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S0045790615000300 | Face detection is one of the most important parts of biometrics and face analysis science. In this paper, a novel multi-stage face detection method is proposed which can remarkably detect faces in different images with different illumination conditions, variety of poses and disparate sizes. The idea is to utilize a preprocessing step to filter many non-face windows by means of a skin segmentation procedure in order to boost the speed of the detection and also utilize the color information as much as possible. Subsequently, candidate windows are fed to a Local Hierarchical Pattern (LHP) generator unit where a new texture pattern is produced. Based on this pattern, a kernel probability map is calculated for each window, and by summing probabilities of all kernels and comparing it with a predefined threshold, decision is made about content of the window. Not only does this algorithm effectively eliminate many non-face regions, but it is also capable of detecting faces with relatively acceptable rate in different conditions. | A face detection method based on kernel probability map |
S0045790615000312 | Mobile Cloud Computing (MCC) augments capabilities of mobile devices by offloading applications to cloud. Resource allocation is one of the most challenging issues in MCC which is investigated in this paper considering neighboring mobile devices as service providers. The objective of the resource allocation is to select service providers minimizing the completion time of the offloading along maximizing lifetime of mobile devices satisfying deadline constraint. The paper proposes a two-stage approach to solve the problem: first, Non-dominated Sorting Genetic Algorithm II (NSGA-II) is applied to obtain the Pareto solution set; second, entropy weight and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method are employed to specify the best compromise solution. Furthermore, a context-aware offloading middleware is developed to collect contextual information and handle offloading process. Moreover, to stimulate selfish users, a virtual credit based incentive mechanism is exploited in offloading decision. The experimental results demonstrate the ability of the proposed resource allocation approach to manage the trade-off between time and energy comparing to traditional algorithms. | Context-aware multi-objective resource allocation in mobile cloud |
S0045790615000324 | Automated recognition of brain tumors in magnetic resonance images (MRI) is a difficult procedure owing to the variability and complexity of the location, size, shape, and texture of these lesions. Because of intensity similarities between brain lesions and normal tissues, some approaches make use of multi-spectral anatomical MRI scans. However, the time and cost restrictions for collecting multi-spectral MRI scans and some other difficulties necessitate developing an approach that can detect tumor tissues using a single-spectral anatomical MRI images. In this paper, we present a fully automatic system, which is able to detect slices that include tumor and, to delineate the tumor area. The experimental results on single contrast mechanism demonstrate the efficacy of our proposed technique in successfully segmenting brain tumor tissues with high accuracy and low computational complexity. Moreover, we include a study evaluating the efficacy of statistical features over Gabor wavelet features using several classifiers. This contribution fills the gap in the literature, as is the first to compare these sets of features for tumor segmentation applications. | Brain tumors detection and segmentation in MR images: Gabor wavelet vs. statistical features |
S0045790615000336 | Wireless multimedia sensor networks (WMSNs) have been used for sensitive applications such as video surveillance and monitoring applications. In a WMSN, storage and transmission become complicated phenomena that can be simplified by the use of compressed sensing, which asserts that sparse signals can be reconstructed from very few measurements. In this paper, memory-efficient measurement matrices are proposed for a discrete wavelet transform (DWT)–discrete cosine transform (DCT) hybrid approach based video compressed sensing (VCS). The performance of the framework is evaluated in terms of PSNR, storage complexity, transmission energy and delay. The results show that the proposed matrices yield similar or better PSNR and consume less memory for generating the matrix when compared with a Gaussian matrix. The DWT–DCT based VCS yields better quality and compression when compared with DCT and DWT approaches. The transmission energy is 50% less and the average delay is 52% less when compared to raw frame transmission. | Video Compressed Sensing framework for Wireless Multimedia Sensor Networks using a combination of multiple matrices |
S0045790615000348 | In this study, a novel single-image based dehazing framework is proposed to remove haze artifacts from images through local atmospheric light estimation. We use a novel strategy based on a physical model where the extreme intensity of each RGB pixel is used to define an initial atmospheric veil (local atmospheric light veil). Across bilateral filter is applied to each veil to achieve both local smoothness and edge preservation. A transmission map and a reflection component of each RGB channel are constructed from the physical atmospheric scattering model. The proposed approach avoids adverse effects caused by the error in estimating the global atmospheric light. Experimental results on outdoor hazy images demonstrate that the proposed method produces image output with satisfactory visual quality and color fidelity. Our comparative study demonstrates a higher performance of our method over several state-of-the-art methods. | Fast single image haze removal via local atmospheric light veil estimation |
S0045790615000506 | Critical infrastructures require protection systems that are both flexible and efficient. Flexibility is essential to capture the multi-organizational and state-based nature of these systems, efficiency is necessary to cope with limitations of hardware resources. To meet these requirements, we consider a classical protection environment featuring subjects that attempt to access the protected objects. We approach the problem of specifying the access privileges held by each subject. Our protection model associates a password system with each object; the password system features a password for each access privilege defined for this object. A subject can access the object if it holds a key matching one of the passwords in the password system, and the access privilege corresponding to this password permits to accomplish the access. Password systems are implemented as hierarchical bidimensional one-way chains. Trade-offs are possible between the memory requirements for storage of a password system and the processing time necessary to validate a key. | Password systems: Design and implementation |
S0045790615000580 | This paper presents a new medical image enhancement method that adjusts the fractional order according to the dynamic gradient feature of the entire image. The presented method can extract the edges of an image accurately and enhance them while preserving smooth areas and weak textures; these improvements can be particularly helpful to doctors’ diagnoses. The primary contribution of this paper is the Adaptive Fractional Differential Algorithm (AFDA), which uses the improved Otsu algorithm to segment the edges, textures and smooth areas of images. This algorithm allows the optimal fractional order of each pixel to be obtained using an adaptive fractional differential function constructed based on the area feature of image. As a result, the image can be enhanced adaptively. Experimental results show that for medical images, AFDA shows better image enhancement than other methods by making edges clearer and textures richer. | Adaptive fractional differential approach and its application to medical image enhancement |
S0045790615000592 | As a part of character recognition, character segmentation (CS) plays an important role in automatic license plate recognition (ALPR) system. In recent years, lots of methods on CS have been proposed and they work well on their own datasets. However, it is still challenging to segment characters from images with frame, declination and quality degradation because of noises and overlapped, connected or fragmented characters. In this paper, we propose a two-stage segmentation method for Chinese license plate. At the first stage, a novel template matching method is presented using a harrow-shaped filter (HSF) bank and minimum response. It finds the locations of the segmenting points between characters roughly. Then, the accurate segmentations between connected or overlapped characters are adjusted by a variant of A∗ path-finding algorithm at the second stage. Experiments on a challenging dataset including 2334 images demonstrate the effectiveness and efficiency of the proposed method. | A two-stage character segmentation method for Chinese license plate |
S0045790615000634 | The biometrics, the password and the storage device are the elements of the three-factor authentication. In 2013, Yeh et al. proposed a three-factor user authentication scheme based on elliptic curve cryptography. However, we find that it has weaknesses including useless user identity, ambiguous process, no session key and no mutual authentication. Also, it cannot resist the user forgery attack and the server spoofing attack. Moreover, Khan et al. propose a fingerprint-based remote authentication scheme with mobile devices. Unfortunately it cannot withstand the user impersonation attack and the De-synchronization attack. Furthermore, the user’s identity cannot be anonymous, either. To overcome the disadvantages, we propose a new three-factor remote authentication scheme and give a formal proof with strong forward security. It could provide the user’s privacy and is secure. Compared to some recent three-factor authentication schemes, our scheme is secure and practical. | A novel and provably secure biometrics-based three-factor remote authentication scheme for mobile client–server networks |
S0045790615000646 | This study proposes a novel optical fiber sensor (OFS) network using three-dimensional (3-D) wavelength/time/spatial optical code-division multiple-access (OCDMA) scheme. The proposed 3-D modified quadratic congruence/M-matrix (MQC/M-matrix) coding scheme overcome the restriction of single pulse per row inherent in traditional three-dimensional codes and maintain a high signal-to-noise ratio even when source power is low. The 3-D system is implemented using optical switches (OSW), fiber-Bragg gratings (FBGs), optical splitter and optical combiner. The noises of phase-induced intensity noise (PIIN) and multiple access interference (MAI) in the decoding mechanism can be suppressed by using a spectral spreading scheme and balance-detection in the receivers. By constructing 3-D codes using bipolar pseudorandom (PN) codes rather than unipolar codes provides a significant increase in the maximum permissible number of active sensor nodes. | A study of three-dimensional optical code-division multiple-access for optical fiber sensor networks |
S0045790615000658 | Backbone nodes are effective for routing in wireless networks because they reduce the energy consumption in sensor nodes. Packet delivery only occurs through the backbone nodes, which depletes the energy in the backbone drastically. Several backbone construction algorithms, including energy-aware virtual backbone tree, virtual backbone tree algorithm for minimal energy consumption and multihop cluster-based stable backbone tree, fail to form a complete backbone when converting important nodes, such as a cut vertex tree node to a non-backbone node. Thus we propose a fault-tolerant virtual backbone tree (FTVBT) algorithm that addresses all of these conflicts and we give theoretical derivations of the bounds for the probability that a sensor node can connect with the backbone. Furthermore, randomized FTVBT improves FTVBT by redistributing non-tree nodes randomly among all the eligible tree nodes based on their fitness values, thereby decreasing the rapid depletion of energy in a particular node and increasing the network lifetime. We performed simulations in NS2 and analyzed the experimental results. | Randomized fault-tolerant virtual backbone tree to improve the lifetime of wireless sensor networks |
S0045790615000683 | The increasing costs of healthcare along with the increasing availability of new Personal Health Devices (PHDs) are the ingredients of the connected health vision. Also, a growing number of consumer electronic and mobile devices are becoming capable of taking the role of a health gateway, thus operating as a data collector for PHDs. In this context, we present a system that enables PHDs to share information in home networks and with the Internet based on a new Internet of Things protocol, namely the Constrained Application Protocol (CoAP). CoAP is used along with the IEEE 11073 family of standards, which is the main exchange data model for PHD communication. We discuss how the proposed system can be integrated to other connected health systems, such as a Universal Plug and Play healthcare system. We detail how the CoAP communication model was adapted to the IEEE 11073 model. We also present a real PHD prototype and its evaluation results. These results demonstrated the feasibility of the proposed solution, showing how its network overhead is around 50% lighter when compared to other protocols. Finally, we tested the proposed solution based on different scenarios, including a proof-of-concept integration with a service in the cloud, using different wireless physical interfaces. | A personal connected health system for the Internet of Things based on the Constrained Application Protocol |
S0045790615000695 | Ubiquitous environments are often considered as highly dynamic environments and contextual information can change at runtime. The user interface should provide the right information for a given user considering runtime context. Such an objective can be achieved only when we deduce the user’s requirements in terms of information and present it to the user according to his current context of use. The overall objective of our research is to generate a user interface adapted to the current context of use for critical fields. This paper explores some key issues related to the architecture of context-aware applications. A formal approach for the analysis of pervasive Human–Computer System (HCS) is presented. XML Petri nets are used to model the pervasive HCS. The proposed approach is illustrated with a case study which presents a hypoglycemic diabetic patient in a “smart hospital”. | A formal approach for modeling context-aware Human–Computer System |
S0045790615000701 | This paper presents our ongoing efforts toward the development of a multi-agent distributed framework for autonomous control of mobile manipulators. The proposed scheme assigns a reactive agent to control each degree-of-freedom of the manipulator(s), a hybrid agent to control the mobile base, and a supervisory agent to coordinate and synchronize the work of the control agents. Each control agent implements a Simulation-Verification technique to optimize, locally and independently from the other agents, a predefined objective function. The final goal consists of bringing the end-effector as close as possible to imposed operational targets (reaching tasks). Different simulation scenarios are described and carried out for the case of RobuTER/ULM robot, with and without considering failures of some articulations of the manipulator or the mobile base. Results show that the main advantage of the proposed approach is that the system pledges a fault-tolerant response to some breakdowns without needing any specific additional treatment. it represents the situation (position and orientation) of the imposed Target it represents the initial/current situation of the end-effector of the robot in the absolute frame. The first three values are the position of the end-effector; the last three represent its orientation angles it corresponds to the new situation of the end-effector after the Move Up/Move Down movement of the joint i of the manipulator it represents the new situation of the end-effector of the robot after the forward/backward/turn left/turn right movement of the mobile base it represents the initial/current/final situation (position and orientation) of the mobile base it represents the new situation of the mobile base after the forward/backward/turn left/turn right movement carried out by the Mobile base agent it corresponds to the initial/current/final configuration of the manipulator joints it corresponds to the new configuration of the manipulator joints after the Move Up/Move Down movement carried out by the Joint agent it represents the initial/current/final (after optimization) value of the objective function | Fault-tolerant multi-agent control architecture for autonomous mobile manipulators: Simulation results |
S0045790615000713 | Traffic accidents are a fact of life. While accidents are sometimes unavoidable, studies show that the long response time required for emergency responders to arrive is a primary reason behind increased fatalities in serious accidents. One way to reduce this response time is to reduce the amount of time it takes to report an accident. Smartphones are ubiquitous and with network connectivity are perfect devices to immediately inform relevant authorities about the occurrence of an accident. This paper presents the development of a system that uses smartphones to automatically detect and report car accidents in a timely manner. Data is continuously collected from the smartphone’s accelerometer and analyzed using Dynamic Time Warping (DTW) and the Hidden Markov Models (HMMs) to determine the severity of the accident, reduce false positives and to notify first responders of the accident location and owner’s medical information. In addition, accidents can be viewed on the smartphone over the Internet offering instant and reliable access to the information concerning the accident. By implementing this application and adding a notification system, the response time required to notify emergency responders of traffic accidents can potentially reduce the response time which may help in reducing fatalities. | iBump: Smartphone application to detect car accidents |
S0045790615000725 | In this paper, we propose a blind color image watermarking scheme based on quaternion discrete Fourier transform (QDFT) and on an improved uniform log-polar mapping (IULPM). The proposed watermarking scheme embeds dual watermarks: one is a meaningful binary image watermark and the other is a bipolar watermark. The former is embedded in the real part of mid-frequency QDFT coefficients using quantization index modulation. The latter is used to resynchronize the watermark after the watermarked image has been attacked, making the scheme resistant to geometric attacks. In particular, the IULPM allows for greater accuracy when estimating the rotation angle of a geometric attack. At the same time, the watermark embedding employs the image holistically, rather than in a block pattern. Experimental results demonstrate that the proposed scheme achieves better performance of robustness against both common signal operations and geometric attacks compared to other existing schemes. | Color image watermarking based on quaternion Fourier transform and improved uniform log-polar mapping |
S0045790615000750 | Recently, audio steganography has become an important covert communications technology. This technology hides secret data in a cover audio without perceptual modification of the cover audio. Most of the existing audio steganography techniques are unsuitable for real-time communication. Although field programmable logic array (FPGA) technologies offer parallel processing in hardware that can improve the speed of steganographic systems, the research activities in this area are very limited. This paper presents a parallel hardware-architecture for dual-mode audio steganography (DMAS) based FPGA technology. The proposed DMAS reconfigures the same hardware blocks in both hiding and recovery modes to reduce the hardware requirements. It has been successfully implemented on a Xilinx XC6SLX16 FPGA board to occupy only 97 slices. Furthermore, it processes data simultaneously at an operating frequency of up to 58.82MHz and accomplishes full message retrieval at an embedding rate of 25% with an audio quality above 45dB in terms of signal to noise ratio. | Concurrent hardware architecture for dual-mode audio steganography processor-based FPGA |
S0045790615000981 | Recently, several image encryption algorithms based on DNA encoding and chaotic maps have been proposed, which create a novel direction in image encryption. By a careful examination on most of these image cryptosystems, we find that DNA operators can only influence one DNA base, which leads to poor diffusion. A recent image encryption scheme based on DNA encoding and chaos is treated as a case study. The flaws of this algorithm are illustrated. By applying a known plaintext attack, we demonstrate that a hacker can determine the chaotic sequences used to confuse the image and reveal the plain-image. Finally, a suggestion is given to enhance the diffusion ability of image encryption scheme based on DNA encoding and chaos. The experiment results prove that the suggestion is effective. | Security analysis on a color image encryption based on DNA encoding and chaos map |
S0045790615000993 | Representation and reasoning about context information is a main research area in Ambient Intelligence (AmI). Context modeling in such applications is facing openness and heterogeneity. To tackle such problems, we argue that usage of semantic web technologies is a promising direction. We introduce CONSERT, an approach for context meta-modeling offering a consistent and uniform means for working with domain knowledge, as well as constraints and meta-properties thereof. We provide a formalization of the model and detail its innovative implementation using techniques from the semantic web community such as ontology modeling and SPARQL. A stepwise example of modeling a commonly encountered AmI scenario showcases the expressiveness of our approach. Finally, the architecture of the representation and reasoning engine for CONSERT is presented and evaluated in terms of performance. | CONSERT: Applying semantic web technologies to context modeling in ambient intelligence |
S0045790615001019 | A major optimization problem in the synthesis of sequential circuits is State Assignment or State Encoding in Finite State Machines (FSMs). The state assignment of an FSM determines the complexity of its combinational circuit and thus area, delay, testability and power dissipation. Since optimal state assignment is an NP-hard problem and existing deterministic algorithms produce solutions far from best known solutions, we resort to the use of non-deterministic iterative optimization heuristics. This paper proposes the use of cuckoo search optimization (CSO) algorithm for solving the state assignment problem (SAP) of FSMs with the aim of minimizing area of the resulting sequential circuit. Results obtained from the CSO algorithm are compared with those obtained from binary particle swarm optimization (BPSO) algorithm, genetic algorithm (GA), and the well-known deterministic methods of NOVA and JEDI. The results indicate that CSO outperforms deterministic methods as well as other non-deterministic heuristic optimization methods. | State assignment for area minimization of sequential circuits based on cuckoo search optimization |
S0045790615001032 | In this paper, we investigate the achievable bit-error-rate performance (BER) of a transmitter preprocessing (TP)-aided cooperative downlink (DL) multi-carrier code division multiple access system by employing three cooperation strategies. In a multi-user cooperative DL communication, multi-user interference at the relays, which prevents the achievement of relay diversity, is suppressed with the aid of the TP operated at the base station (BS). In addition, inter-relay interference at the destination mobile station is mitigated by the TP employed at the relays. Furthermore, the channel impulse responses (CIRs) required for formulating the TP at the BS is based on the quantized CIRs feedback in contrast to the perfect CIRs (PCIRs) assumption at the relays. Our study shows that the resultant BER performance of the quantized CIRs feedback-based TP at the BS, coupled with the PCIR-based TP at the relays, remains close to that attained with the PCIRs knowledge at the BS and relays. | Performance of Relay-Aided Multi-Carrier-CDMA using preprocessing based on quantized feedback |
S0045790615001056 | This paper addresses the problem of identifying meaningful patterns and trends in data via clustering (i.e. automatically dividing a data set into meaningful homogenous sub-groups such that the data within the same sub-group are very similar, and data in different sub-groups are very different). The clustering framework that we propose is based on the generalized Dirichlet distribution, which is widely accepted as a flexible modeling approach, and a hierarchical Dirichlet process mixture prior. A main advantage of the adopted hierarchical Dirichlet process is that it provides a principled elegant nonparametric Bayesian approach to model selection by supposing that the number of mixture components can go to infinity. In addition to capturing the structure of the data, the combination of hierarchical Dirichlet process and generalized Dirichlet distribution is shown to offer a natural efficient solution to the feature selection problem when dealing with high-dimensional data. We develop two variational learning approaches (i.e. batch and incremental) for learning the parameters of the proposed model. The batch algorithm examines the entire data set at once while the incremental one learns the model one step at a time (i.e. update the model’s parameters each time new data are introduced). The utility of the proposed approach is demonstrated on real applications namely face detection, facial expression recognition, human gesture recognition, and off-line writer identification. The obtained results show clearly the merits of our statistical framework. | A hierarchical Dirichlet process mixture of generalized Dirichlet distributions for feature selection |
S0045790615001068 | Modalities other than GPS need to be employed to localize mobile sensor-node-enabled subjects in indoor conditions. The location of some mobile nodes needs to be computed precisely while this may not be essential for the remaining nodes. We have proposed the concept of graded precision localization which allows mobile nodes to localize themselves to heterogeneous precision levels in a common framework. With graded precision localization, we define a modular node for the subjects, specify deployment strategies customizable for each site, and propose a framework for evaluating site-specific localization performance. We comprehensively evaluate graded precision localization with experiments and simulation for indoor conditions, and highlight its advantages over similar systems. | Performance evaluation of graded precision localization with sensor networks in indoor spaces |
S0045790615001081 | Service-oriented architecture (SOA) is a self-contained service with a collection of services. Services communicate with each other using a web service. Web services use a collection of open protocols and standards for communication between different web services and their applications. In today’s environment, users are not satisfied with a single web service. To fulfill the users’ needs, two or more atomic services must be combined to provide a single complex service. Hence several atomic web services must be orchestrated based on user preference by using a multi-agent system. In the traditional approach, the orchestration of web services is a manual process. The proposed system reduces human intervention and supports the orchestration of atomic web services into a complex service by using a multi-agent system. Therefore, this paper addresses the automatic orchestration by using a multi-agent i.e., two agents. The first agent is used to select an appropriate web service from the available atomic service. The second agent is used to orchestrate the selected web services to form a complex service based on a user’s requirement and quality of service (QoS). | User preference-based automatic orchestration of web services using a multi-agent |
S0045790615001111 | Anycast is an important way of communication for Mobile Ad hoc Networks (MANETs) in terms of resources, robustness and efficiency for replicated service applications. Most of the anycast routing protocols select unstable and congested intermediate nodes, thereby causing frequent path failures and packet losses. We propose a mobility and quality of service aware anycast routing scheme in MANETs (MQAR) that employs three models: (1) node movement stability, (2) channel congestion, and (3) link/route expiry time. These models coupled with Dynamic Source Routing (DSR) protocol are used in the route discovery process to select nearest k-servers. A server among k-servers is selected based on less congestion, route expiry time, number of hops, and better stability. The simulation results indicate that proposed MQAR demonstrates, reduction in control overheads, path delays and improved packet delivery ratio compared to existing methods such as flooding, DSR and load balanced service discovery. | Mobility and QoS aware anycast routing in Mobile ad hoc Networks |
S0045790615001123 | A Mobile Ad hoc Network (MANET) is an infrastructure-less collection of nodes that are powered by portable batteries. Consumption of energy is the major constraint in a wireless network. This paper presents a new algorithm called Energy-Aware Span Routing Protocol (EASRP) that uses energy-saving approaches such as Span and the Adaptive Fidelity Energy Conservation Algorithm (AFECA). Energy consumption is further optimized by using a hardware circuit called the Remote Activated Switch (RAS) to wake up sleeping nodes. These energy-saving approaches are well-established in reactive protocols. However, there are certain issues to be addressed when using EASRP in a hybrid protocol, especially a proactive protocol. Simulation results for the EASRP protocol show an increase in energy efficiency of 12.2% and 17.45% compared with EAZRP and ZRP, respectively. The EASRP protocol also proves to be effective in by producing a better packet delivery ratio for low- and high-density networks as measured by the NS-2 simulation tool. | A new routing protocol for energy efficient mobile applications for ad hoc networks |
S0045790615001135 | This research proposes a framework for a real time implementation of a Brain Computer Interface (BCI). This interface is designed with a future objective of providing a testing platform as an interactive and intelligent Image Search and Retrieval tool that allows users, disabled or otherwise, to browse and search for images using non-invasive electroencephalography (EEG) signals. As a proof of concept, a prototype system was designed and implemented to test real time data collection and navigation through the interface by detection and classification of event-related potentials (ERPs). A comparison of different feature extraction methods and classifiers for the detection of ERPs is performed on a standard data set to determine the best fit for the real time implementation of the BCI. The preliminary results of the real time implementation of the prototype BCI system are quantified by the success rate of the user/subject in navigating through the interface and spelling a search keyword using the mental-typewriter Hex-O-Speller. | A framework for a real time intelligent and interactive Brain Computer Interface |
S0045790615001147 | An improved image magnification algorithm for gray and color images is presented in this paper to meet the challenge of preserving high-frequency components of an image, including both image edges and texture structures. In the proposed algorithm, a new edge detection method that uses the well-known Otsu automatic optimum thresholding is proposed to distinguish strong edge pixels. The parameters of the original directional cubic convolution interpolation algorithm, which were selected based on training, were eliminated. As a result, our algorithm achieves more accurate edge detection, better interpolation results, and less computational complexity. Simulation results demonstrate that the improved algorithm can reconstruct the magnified image, preserve edges and textures simultaneously, and reduce common interpolation artifacts. Furthermore, it generates higher visual quality of the magnified images and achieves higher peak signal-to-noise ratio, structural similarity, and feature similarity compared with other state-of-the-art methods. | Improved image magnification algorithm based on Otsu thresholding |
S0045790615001159 | This article presents a new method for detecting objects on waters’ surfaces using colour elimination based on image erosion with a morphological variable. The proposed object detection method includes definitions of the target’s colour space and colour deviation using Euclidean distance. It also introduces a procedure for image erosion using a morphological variable. In order to evaluate the proposed object detection method, the experiments were performed on two different image databases: the MSRA (Microsoft Research Asia) salient object database and a proprietary image database containing pictures of water activities typically encountered near hydro power plants. The experimental results show that the proposed object detection method enables efficient and robust detection of objects on of waters’ surfaces, compared to other methods primarily based on the optimisation of image contrast and edge detection. | Detection of objects on waters’ surfaces using CEIEMV method |
S0045790615001238 | Key distribution is required to secure e-health applications in the context of Internet of Things (IoT). However, resources constraints in IoT make these applications unable to run existing key management protocols. In this paper, we propose a new lightweight key management protocol. This protocol is based on collaboration to establish a secure end-to-end communication channel between a highly resource constrained node and a remote entity. The secure channel allows the constrained node to transmit captured data while ensuring confidentiality and authentication. To achieve this goal, we propose offloading highly consuming cryptographic primitives to third parties. As a result, the constrained node obtains assistance from powerful entities. To assess our protocol, we conduct a formal validation regarding security properties. In addition, we evaluate both communication and computational costs to highlight energy savings. The results show that our protocol provides a considerable gain in energy while its security properties are ensured. | An end-to-end secure key management protocol for e-health applications |
S0045790615001251 | This study develops a hierarchical scheme with three processing layers for human behavior recognition. The proposed scheme is an audio-based approach that employs a microphone array of the Kinect sensor for sensing and acquiring acoustic data to classify human behavior. The three processing layers, namely the feature layer, acoustic event classification layer, and specific behavior recognition layer, are interrelated, and the sensing data fusion, Gaussian mixture model with a classification tree, and state machine diagram to regulate human behavior are employed in these three layers, respectively. With enhanced performance of the feature and acoustic event classification layers, the proposed scheme exhibits increased human behavior classification accuracy. Human behavior recognition experiments were conducted in a research office, and three specific office behavior modes, namely “Laboratory meeting,” “Classmate chatting,” and “Laboratory study interaction,” were effectively classified using the proposed method. | Three-layered hierarchical scheme with a Kinect sensor microphone array for audio-based human behavior recognition |
S0045790615001263 | Multiple-Input Multiple-Output system plays a major role in the fourth generation wireless systems to provide high data rates. In this paper, a blind channel estimation approach has been proposed for finding the channel length based on the signals received from the MIMO (Multiple-Input Multiple-Output) transceiver. The resultant MIMO channel length information is utilized for estimation of the channel impulse response of the system. The estimation is used for adaptation of the equalizer weights, based on the proposed Constant Modulus Algorithm which has reduced the fading and multipath propagation resulting from Inter Symbol Interference. The performance of the proposed system has been analyzed in terms of Mean Square Error and Symbol Error Rate for various Signal to Noise Ratio. | Blind channel estimation for Multiple-Input Multiple-Output system using Constant Modulus Algorithm |
S0045790615001275 | Advances in wireless ad-hoc network techniques have spurred the development of new approaches to increase network efficiency. One of the more popular approaches is swarm intelligence. Swarm intelligence imitates the collective behavior of biological species to solve network routing problems. Meanwhile, weakly connected dominating sets (WCDS) can serve as auxiliary structures for clustering nodes in the network. This paper uses the clustering concept of WCDS to propose an improved ant-based on-demand clustering routing (AOCR) protocol for wireless ad-hoc networks. Network states’ information is obtained from the Forward_Ant, and is only broadcast by the head of every cluster, thus decreasing the overhead required to transmit ant packets. To increase network efficiency, the pseudo-random-proportional-selection strategy is used to evaluate the best path from the source node to the destination node by the Backward_Ant. | Weakly connected dominating set-assisted ant-based routing protocol for wireless ad-hoc networks |
S0045790615001287 | Power consumption is emerging as one of the main concerns in the High Performance Computing (HPC) field. As a growing number of bioinformatics applications require HPC techniques and parallel architectures to meet performance requirements, power consumption arises as an additional limitation when accelerating them. In this paper, we present a comparative study of optimized implementations of the Non-negative Matrix Factorization (NMF), that is widely used in many fields of bioinformatics, taking into account both performance and power consumption. We target a wide range of state-of-the-art parallel architectures, including general-purpose, low-power processors and specific-purpose accelerators like GPUs, DSPs or the Intel Xeon Phi. From our study, we gain insights in both performance and energy consumption for each one of them under a number of experimental conditions, and conclude that the most appropriate architecture is usually a trade-off between performance and energy consumption for a given experimental setup and dataset. | Non-negative Matrix Factorization on Low-Power Architectures and Accelerators: A Comparative Study |
S0045790615001299 | Geometric distortions are more difficult to tackle than other types of attacks. It is a challenging work to design a robust image watermarking scheme against geometric distortions. In this paper, we propose a robust digital image watermarking scheme based on local polar harmonic transform. The proposed scheme has the following advantages: (1) the stable and uniform image feature points are extracted by the improved speeded-up robust feature (SURF) detector, in which the probability density gradient is utilized, (2) the affine invariant local feature regions are constructed adaptively according to the variation of local probability density, and (3) a new and effective 2D transform, named polar harmonic transform (PHT), is introduced to embed watermark in the digital image. Experiments are carried out on a digital image set of 100 images collected from Internet, and the preliminary results show that the proposed image watermarking is not only invisible and robust against common image processing operations such as filtering, noise adding, and JPEG compression, but also robust against the geometric distortions. | A new robust digital watermarking using local polar harmonic transform |
S0045790615001317 | One of the primary objectives of Wireless Sensor Network (WSN) is to provide full coverage of a sensing field as long as possible. The deployment strategy of sensor nodes in the sensor field is the most critical factor related to the network coverage. However, the traditional deployment methods can cause coverage holes in the sensing field. Therefore, this paper proposes a new deployment method based on Multi-objective Immune Algorithm (MIA) and binary sensing model to alleviate these coverage holes. MIA is adopted here to maximize the coverage area of WSN by rearranging the mobile sensors based on limiting their mobility within their communication range to preserve the connectivity among them. The performance of the proposed algorithm is compared with the previous algorithms using Matlab simulation for different network environments with and without obstacles. Simulation results show that the proposed algorithm improves the coverage area and the mobility cost of WSN. | Rearrangement of mobile wireless sensor nodes for coverage maximization based on immune node deployment algorithm |
S0045790615001329 | BPEL or Business Process Execution Language is so far the most important standard language for effective composition of Web services. However, like most available process orchestration engines, BPEL does not provide automated support for reacting according to many changes that are likely to arise in any Web services composition, like downtime services, modifications in the business logic or even new policies to govern the composition. Also low-level specification of these new changes, which would be integrated at runtime in the BPEL process, will be far from being used conveniently. Moreover, the complexity of interaction in composite Web services and the diversity of rules and policies can lead to critical behavioral conflicts. We propose in this paper AOMD, a novel aspect-oriented and model driven approach that defines new grammar to address both adaptability and behavioral conflicts problems, and offers extension for WS-BPEL meta-model for high level specification of aspects. Further, we formally verify our proposition and we present real life case study, examples and experimental results that demonstrate the feasibility and effectiveness of our work. | AOMD approach for context-adaptable and conflict-free Web services composition |
S0045790615001330 | In this paper, we propose GeoRank, a geographic routing approach for the IPv6-enabled large-scale low-power and lossy networks. We discuss the main drawbacks of the RPL (IPv6 Routing Protocol for Low-Power and Lossy Networks) for P2P (point-to-point) communication in large-scale 6LoWPAN networks. Then, we address such drawbacks by proposing a routing protocol, named GeoRank, which integrates RPL protocol with the position-based routing protocol GOAFR (Greedy Other Adaptive Face Routing). The results obtained with simulations show that GeoRank finds shorter routes than RPL in high link density conditions and than GOAFR in low link density conditions. Thus, GeoRank shows to be adaptive to variable link densities found in large-scale networks. Further, GeoRank avoids the use of DAO (Destination Advertisement Object) control messages required in RPL, while being more scalable in terms of memory usage than storing-mode RPL. | A geographic routing approach for IPv6 in large-scale low-power and lossy networks |
S0045790615001342 | Genetic programming (GP) is an evolutionary method that allows computers to solve problems automatically. However, the computational power required for the evaluation of billions of programs imposes a serious limitation on the problem size. This work focuses on accelerating GP to support the synthesis of large problems. This is done by completely exploiting the highly parallel environment of graphics processing units (GPUs). Here, we propose a new quantum-inspired linear GP approach that implements all the GP steps in the GPU and provides the following: (1) significant performance improvements in the GP steps, (2) elimination of the overhead of copying the fitness results from the GPU to the CPU, and (3) incorporation of a new selection mechanism to recognize the programs with the best evaluations. The proposed approach outperforms the previous approach for large-scale synthetic and real-world problems. Further, it provides a remarkable speedup over the CPU execution. | Use of graphics processing units for automatic synthesis of programs |
S0045790615001366 | The use of computational accelerators such as NVIDIA GPUs and Intel Xeon Phi processors is now widespread in the high performance computing community, with many applications delivering impressive performance gains. However, programming these systems for high performance, performance portability and software maintainability has been a challenge. In this paper we discuss experiences porting applications to the Titan system. Titan, which began planning in 2009 and was deployed for general use in 2013, was the first multi-petaflop system based on accelerator hardware. To ready applications for accelerated computing, a preparedness effort was undertaken prior to delivery of Titan. In this paper we report experiences and lessons learned from this process and describe how users are currently making use of computational accelerators on Titan. | Accelerated application development: The ORNL Titan experience |
S0045790615001378 | Malaria, one of the deadliest diseases, is responsible for nearly 627,000 deaths every year. It is diagnosed manually by pathologists using a microscope. It is time-consuming and subjected to inconsistency due to human intervention, so computerized image analysis for diagnosis has gained importance. In this article, an edge-based segmentation of erythrocytes infected with malaria parasites using microscopic images has been developed to facilitate the diagnostic process. The color space transformation and Gamma equalization reduce the effects of colors and correct luminance differences of images. Fuzzy C-means clustering is applied to extract infected erythrocytes, which is further processed for the final segmentation. The experimental results showed that the proposed method can gain 98%, 93.3%, 98.65% and 90.33% of sensitivity, specificity, prediction value positive and prediction value negative, respectively. In conclusion, the proposed method provides a consistent and robust method of edge-based segmentation of parasite infected erythrocytes using microscopic images for diagnosis. | Segmentation of erythrocytes infected with malaria parasites for the diagnosis using microscopy imaging |
S0045790615001391 | Accurate image retrieval is required to index and retrieve large number of images from huge databases. In this paper, an efficient approach is presented to encode the color and textural features of images from the local neighborhood of each pixel. The color features are extracted by quantizing the RGB color space into a single channel with reduced number of shades. The texture information is encoded with structuring patterns generated from the locally structured elements chosen as a basis. Color and textural features are fused together to construct the inherently rotation and scale-invariant hybrid image descriptor (RSHD). This fusion is carried out by extracting textural cues over each shade independently. RSHD has been tested on the Corel dataset and experimental results suggest that RSHD outperforms state-of-the-art descriptors. The performance of the RSHD is promising under rotation and scaling. It can also be effectively used under more complex image transformations. | Rotation and scale invariant hybrid image descriptor and retrieval |
S0045790615001408 | The paper deals with the level control of a Modified Quadruple Tank Process (MQTP). In that, the interaction is introduced between the bottom two tanks which causes an additional non-linear dynamical component of the conventional Quadruple Tank Process (QTP). Since the process has an inbuilt and imposed uncertainties, a robust Sliding Mode Controller (SMC) is initially designed to drive the system to the desired operating point via the sliding surface. Further, the conventional sliding surface is altered with fractional order dynamics. It makes a Fractional-Order SMC (FrSMC) and is proposed for both finite time convergence and counteract to the uncertainties present in the system. The undesirable chattering effect is reduced by introducing a novel exponential Multi-Level Switching (MLS) technique in order to protect control valve. Simulation results show the efficacy of the proposed Multi-Level Switching FrSMC (MFrSMC) in terms of fast convergence with high robustness when compared to conventional SMC. | Fractional-Order Sliding Mode Controller Design for a Modified Quadruple Tank Process via Multi-Level Switching |
S0045790615001421 | Steganography has become a hot topic in information hiding, and the reversibility technology allows the recovery of the original image without distortion when the embedded secret information is extracted. In this paper, a high payload image steganographic scheme based on an extended interpolating method is proposed. In the premise of image quality assurance, the proposed scheme increases the capacity by maximizing the difference between neighboring pixels. Meanwhile, it has low complexity and retains good image quality. Extensive experiments on images have been conducted and the experimental results demonstrate that the proposed approach performs better than several state-of-the-art methods. | Reversible steganography using extended image interpolation technique |
S0045790615001433 | An assessment approach to assess the likelihood of rock burst in coal mines by integrating the Multi-Agent System with data fusion techniques is proposed in this paper. We discuss an optimal algorithm for multi-sensor data fusion to improve the accuracy and reliability of the source data. Some model-based situation quantization methods are described and a rock burst situation quantitative assessment model incorporating improved Dempster–Shafer theory is presented. The Auto-Regressive, Moving Average and Holt–Winters models are used to address indefinability and inaccuracy of the prediction. A case study demonstrates that the proposed situation assessment model is capable of producing relatively accurate forecasts, and thereby it can provide coal mine decision-makers with an overview of the development of rock bursts. | A situation assessment method for rock burst based on multi-agent information fusion |
S0045790615001445 | Cloud computing provides an effective approach to deliver multimedia services to end users with the desired user quality of experience (QoE). However, cloud-based multimedia applications require many of servers and consume huge energy. To reduce energy consumption, a multimedia service provider (MSP) should balance the energy and QoE. In this paper, a theoretic model is developed to explore the trade-off between energy consumption and QoE for multimedia cloud. Based on objective factor, a QoE quantifying model is proposed. Employing Lyapunov Optimization techniques, an optimal control framework is designed and analyzed to make energy and QoE decisions in MSPs. An approximate online algorithm (EUE-RP) is proposed with the explicitly provable performance upper bound. Extensive experiments have been conducted to verify the effectiveness of EUE-RP algorithm in the practical settings. The algorithm can guarantee desired QoE and reduce energy consumption, even without any information about the future fluctuation of user demands. | Tradeoff between energy and user experience for multimedia cloud computing |
S0045790615001457 | Affine Transform (AT) is widely used in high-speed image processing systems. This transform plays an important role in various high-speed image processing applications. AT, an important process during the intensity-based image registration, is applied iteratively during the registration. This is also used for the analysis of the interior of an organ and to get a better view of the organs from various angles in 3D coordinate system. Hence, for real-time medical image registration and visualization of the acquired volumetric images, acceleration of AT is very much sought for. In this paper, a parallel and pipelined architecture of the proposed AT algorithm has been presented. This will accelerate the transform process and reduce the processing time of medical image registration. The architecture is mapped in Field-Programmable Gate Array (FPGA) for prototyping and verification. The results show that the computational complexity of the proposed parallel algorithm is almost 4 times better than that of the conventional algorithm. | FPGA based accelerated 3D affine transform for real-time image processing applications |
S0045790615001469 | Inter-Cell Interference (ICI) from neighboring cells is the major challenge that degrades the performance of Orthogonal Frequency Division Multiple Access (OFDMA) cellular mobile systems, particularly for cell edge users. An efficient technique to mitigate ICI is the interference coordination. The most commonly ICI Coordination (ICIC) technique is the Fractional Frequency Reuse (FFR), which effectively mitigates ICI by applying different reuse factors to Users’ Equipments (UEs) situated in different regions in each cell. This paper presents a novel Self-Organized FFR Resource Allocation (SORA) scheme that automatically selects the optimal RA to inner and outer regions of the cell, based on coordination between neighboring evolved NodeBs (eNBs), through a message passing approach over Long Term Evolution (LTE)-X2 interfaces. The performance of the proposed scheme is evaluated using MATLAB and compared with different combinations of RA as well as with frequency reuse-1 and reuse-3 schemes. Simulation results show that the proposed scheme improves the cell-edge performance and achieves high degree of fairness among UEs compared to reference RA schemes. | Self-organized dynamic resource allocation using fraction frequency reuse scheme in long term evolution networks |
S0045790615001470 | With the rapid advancement in very large scale integration (VLSI) technology, it is the utmost necessity to achieve a reliable design with low power consumption. The Quantum dot Cellular Automata (QCA) can be such an architecture at nano-scale and thus emerges as a viable alternative for the current CMOS VLSI. This work targets design of logic module in QCA. It reports a modular design methodology to build the fault tolerant 2 n :1 multiplexer with optimized wire-crossings, delay and power consumption. A 2:1 QCA multiplexer is proposed as the basic logic module that in turn is utilized to synthesize 4:1 and 8:1 multiplexers. It shows significant achievement in terms of clock speed (36%), wire-crossing (58%), fault tolerance (77.62%) and power consumption over the existing designs. The effectiveness of proposed multiplexer is further established through synthesis of configurable logic block (CLB) for field programmable gate arrays (FPGAs). | Towards modular design of reliable quantum-dot cellular automata logic circuit using multiplexers |
S0045790615001482 | We propose a new optical reconfigurable Network-on-Chip (NoC), named ReFaT ONoC (Reconfigurable Flat and Tree Optical NoC). ReFaT is a dynamically reconfigurable architecture, which customizes the topology and routing paths based on the application characteristics. ReFaT, as an all-optical NoC, routes optical packets based on their wavelengths. For this purpose, we propose a novel architecture for the optical switch, which eliminates the need for optical resource reservation, and thus avoids the corresponding latency and area overheads. As a key idea for dynamic reconfiguration, each application is mapped to a specific set of wavelengths and utilizes its dedicated routing algorithm. We compare the proposed reconfigurable optical NoC with traditional electrical NoCs, as well as non-reconfigurable optical NoCs in terms of data transmission delay, power consumption, and energy dissipation. The simulation results show that on average, ReFaT reduces power and energy consumption by 54.75% and 40%, respectively, compared to the non-reconfigurable ONoC. | Application-based dynamic reconfiguration in optical network-on-chip |
S0045790615001494 | Manycore CMP systems are expected to grow to tens or even hundreds of cores. In this paper we show that the effective co-design of both, the network-on-chip and the coherence protocol, improves performance and power meanwhile total area resources remain bounded. We propose a snoopy-aware network-on-chip topology made of two mesh-of-tree topologies. Reducing the complexity of the coherence protocol – and hence its resources – and moving this complexity to the network, leads to a global decrease in power consumption meanwhile area is barely affected. Benefits of our proposal are due to the high-throughput and low delay of the network, but also due to the simplicity of the coherence protocol. The proposed network and protocol minimizes communication amongst cores when compared to traditional solutions based either on 2D-mesh topologies or in directory-based protocols. | Area-efficient snoopy-aware NoC design for high-performance chip multiprocessor systems |
S0045790615001500 | Progress in the area of environmental sustainability for the mobile computing industry could be achieved by making advancement on two fronts: reducing the energy consumed by individual devices throughout their life cycle and reducing the rate at which these devices are discarded. In this work, to address both fronts, we propose the use of a thin-client approach, whereby a mobile device relies mainly on the resources at a remote server to carry out application tasks. To assess the benefits of the proposed approach, this work develops an analytical model as well as performs an empirical evaluation of performance and energy consumption on Android-based smartphones. In terms of energy, a reduction of approximately 11% in the average life cycle energy (LCE) is seen by increasing the device’s usage life by even three months through a thin-client approach. In terms of performance, a thin-client device is shown to improve execution by 57% compared to a self-reliant device. | Thin is green: Leveraging the thin-client paradigm for sustainable mobile computing |
S0045790615001512 | Based on previous results on periodic non-uniform sampling (Multi-Coset) and using the well known Non-Uniform Fourier Transform through Bartlett’s method for Power Spectral Density estimation, we propose a new smart sampling scheme named the Dynamic Single Branch Non-uniform Sampler. The idea of our scheme is to reduce the average sampling frequency, the number of samples collected, and consequently the power consumption of the Analog to Digital Converter. In addition to that our proposed method detects the location of the bands in order to adapt the sampling rate. In this paper, through we show simulation results that compared to classical uniform sampler or existing multi-coset based samplers, our proposed sampler, in certain conditions, provides superior performance, in terms of sampling rate or energy consumption. It is not constrained by the inflexibility of hardware circuitry and is easily reconfigurable. We also show the effect of the false detection of active bands on the average sampling rate of our new adaptive non-uniform sub-Nyquist sampler scheme. | Adaptive non-uniform sampling of sparse signals for Green Cognitive Radio |
S0045790615001536 | Cooperative spectrum sensing is a process of achieving spatial diversity gain to make global decision for cognitive radio networks. However, accuracy of global decision effects owing to the presence of malicious users/nodes during cooperative sensing. In this work, an extended generalized extreme studentized deviate (EGESD) method is proposed to eliminate malicious nodes such as random nodes and selfish nodes in the network. The random nodes are carried off based on sample covariance of each node decisions on different frames. Then, the algorithm checks the normality of updated soft data using Shapiro–Wilk test and estimates the expected number of malicious users in cooperative sensing. These are the two essential input parameters required for classical GESD test to eliminate significant selfish nodes accurately. Simulation results reveal that the proposed algorithm can eliminate both random and frequent spectrum sensing data falsification (SSDF) attacks in cooperative sensing and outperforms the existing algorithms. | Efficient elimination of erroneous nodes in cooperative sensing for cognitive radio networks |
S0045790615001548 | In this paper, we present two novel interference management stratagems for coexisting one primary user (PU) and multiple secondary users (SUs) by exploiting the unused spatial directions at PU. The cognitive stations sense their environment to determine the users they are interfering with, and adapt to it by designing the corresponding precoders using interference alignment (IA) in order to avoid causing performance degradation to nearby PU and SUs. The first proposed approach judiciously designs the set of precoders based on an improved version of minimum weighted leakage interference algorithm. However, there are still leftover interference signals in SUs’ desired signal space due to the limited iterative times in the first algorithm. To tackle this problem, another scheme combining the first one and power allocation method at the secondary stations is developed. Numerical results validate the effectiveness of the proposed algorithms. | Precoding design for interference mitigation in cognitive radio networks based on matrix distance |
S0045790615001573 | In order to retrieve an image from a large image database, the descriptor should be invariant to geometric transformations (e.g., rotation, scaling, and translation). It must also have enough discriminating power and immunity to noise for retrieval from a large image database. The Exponent moments (EMs) descriptor has many desirable properties such as expression efficiency, robustness to noise, geometric invariance, fast computation, and multi-level representation. In this paper, we analyze the rotation, scaling, and translation (RST) invariant property of EMs, and propose a content-based image retrieval approach using invariant EMs. Experimental results show that the EMs can be used as an effective descriptor of global image content, and the proposed retrieval approach yields higher retrieval accuracy than some current state-of-the-art retrieval methods. | Color image representation using invariant exponent moments |
S0045790615001780 | Indefinite and uncontrollable growth of cells leads to tumors in the brain. The early diagnosis and proper treatment of brain tumors are essential to prevent permanent damage to the brain or even patient death. Accurate data regarding the position of the tumor and its size are essential for effective treatment. Hence, an entirely computerized automatic system to provide accurate tumor data is compulsory for physicians. Such developments are necessary to diagnose brain tumors during brain surgery. Brain magnetic resonance (MR) images are proposed for the detection and segmentation of the tumor region via a completely automatic and highly accurate method. The approach discussed in this paper employs an adaptive neuro fuzzy inference system (ANFIS) based on the automatic seed point selection range. The pixels intensity of the proposed algorithm is not dependent on the tumor type. The tumor’s segmentation results are evaluated based on various criteria, including similarity index (SI), overlap fraction (OF), extra fraction (EF) and positive predictive value (PPV), which corresponded to values of 0.817%, 0.817%, 0.182%, and 0.817%, respectively, in this study. These results indicate that the approach proposed in this study performs better compared to many conventional processes. The significance of this work is the differentiation of brain abnormalities from the healthy brain tissue. | Performance analysis of classifier for brain tumor detection and diagnosis |
S0045790615001792 | Automating actions based on collected context from Internet of Things (IOT)-controlled systems is one of the most important requirements of IOT systems; this paper seeks to satisfy this requirement by offering a context-aware service framework on top of IOT controlled systems. The fault management process in electric power distribution networks is taken here as a case study and used for implementing our proposed framework. We discuss the different aspects that need to be covered in such a framework and its components. The obtained results from simulating and testing the framework show a significant improvement in the task management process compared to the traditional approach. | A context-aware dispatcher for the Internet of Things: The case of electric power distribution systems |
S0045790615001809 | In a wireless sensor network where sensors are arranged into a flat topology, sensors near the sink consume much more energy than sensors at the boundary of the network. Sensors near the sink relay many packets than far away sensors to the sink. After these sensors expire, energy holes are created near the sink. Therefore, other sensors cannot reach to the sink and the network becomes disconnected. In this paper, we propose some strategies that can balance energy consumption of the deployed sensors and reduce energy holes from the network by balancing the communication load as equally as possible. We performed extensive experiments on the proposed algorithm using various network scenarios and compared it with other existing algorithms. The experimental results verify the effectiveness and feasibility of the proposed work in terms of network lifetime, energy consumption, and other important network parameters. | Load management scheme for energy holes reduction in wireless sensor networks |
S0045790615001810 | Detecting the linear features in an image is a key technology for different applications. In this paper, a simple and effective algorithm based on the hit-or-miss transform is proposed. To detect linear features with different directions, multi-structuring elements corresponding to different directions are constructed. To detect linear features with different widths, a multi-scale extension of the constructed multi-structuring elements is used. Then, the grey-level hit-or-miss transform that utilizes the constructed multi-scales of multi-structuring elements could effectively extract all of the possible linear features without thresholding. Therefore, after refining the extracted linear feature regions using three simple steps, the final linear features could be effectively detected. Experimental results on different images from different applications show that the proposed algorithm performs well for detecting linear features with different widths, different grey distributions and noises. | Linear feature detection based on the multi-scale, multi-structuring element, grey-level hit-or-miss transform |
S0045790615001822 | Spectrum sensing is an important aspect of cognitive radios. This paper describes a method for spectrum sensing based on the autocorrelation of the received samples. The proposed method was evaluated by means of experiments wherein the probabilities of detection and false alarm at different signal-to-noise ratios (SNRs) were observed. The platform used for the experiments was a set of Universal Software Radio Peripheral™ (USRP™) devices acting as radio frequency front ends in combination with GNU Radio software. Since the signal processing was performed in the software domain, Gaussian noise of different levels was emulated by changing the standard deviation of a Python random number generator. In addition, the output power of a signal generator was varied to obtain different levels of SNR. A metric called the Euclidean distance was derived to analyze the autocorrelation of the samples received by the USRP™ device in order to decide between two possible situations: only noise present or signal plus noise present. The proposed method was compared with two methods: one based on the value of the autocorrelation at the first lag and another one based on the power of the signal, known as energy detection spectrum sensing technique. | A spectrum sensing technique based on autocorrelation and Euclidean distance and its comparison with energy detection for cognitive radio networks |
S0045790615002050 | Image contrast enhancement and brightness preservation are fundamental requirements for many vision based applications. However, these are two conflicting objectives when the image is processed by histogram equalization approaches. Current available methods may not provide results simultaneously satisfying both requirements. In this work, a pipelined approach including color channel stretching, histogram averaging and re-mapping is developed. By using stretching, color information from a scene is restored. Averaging against a uniform distribution enables the output image to recover the information lost. Furthermore, histogram re-mapping reduces artifacts that often arise from the equalization procedure. The technique also employs a search process to find optimal algorithmic parameters, such that the mean brightness difference between the input and output images is minimized. The effectiveness of the proposed method was tested with a set of images captured in adverse environments and compared against available methods. High performing qualitative and quantitative results were obtained. | Image enhancement using the averaging histogram equalization (AVHEQ) approach for contrast improvement and brightness preservation |
S0045790615002074 | In this paper, we propose a systematic rateless erasure code, namely systematic Random (SYSR) code based on Random code for short messages transmission. Given a message of k symbols, the sender will first send the message to the receiver as Part I coded symbols. The rest of coded symbols starting from k + 1 th onwards are termed as Part II coded symbols and they are generated by adding the message symbols randomly (XOR operation). The receiver reconstructs the original message instantly if all the Part I coded symbols are received intact. Otherwise, the receiver reconstructs the original message from any k + 10 coded symbols of Part I and II with high probability of complete decoding (PCD), i.e. 99.9% success probability. Though SYSR code inherits the high decoding complexity of Random code, i.e. O ( k 3 ) , both analysis and simulation results show that SYSR code achieves better PCD and fewer decoding steps than Random code. | Systematic rateless erasure code for short messages transmission |
S0045790615002086 | Power efficiency is a crucial issue for embedded systems, and effective power profiling and prediction tools are in high demand. This paper presents a cloud-based power profiling (CPP) tool for recording system calls and their associated parameters to predict hardware power consumption when running target applications. Based on hardware power consumption and system profiling from the operating system (OS) kernel, the proposed network model can effectively summarize running behavior of the target applications and the relationship among system calls. This model is also used to develop an energy efficient cluster scheduling for user-inactive processes to reduce the power consumption and extend the service time of embedded systems. These profiling data can be integrated into a cloud model to be maintained by software designers or OS developers to accommodate power estimation and scheduling data for a variety of platforms. | Cloud-based power estimation and power-aware scheduling for embedded systems |
S0045790615002116 | In this paper we present a novel pose and expression invariant approach for 3D face registration based on intrinsic coordinate system characterized by nose tip, horizontal nose plane and vertical symmetry plane of the face. It is observed that distance of nose tip from 3D scanner is reduced after pose correction which is presented as a quantifying heuristic for proposed registration scheme. In addition, motivated by the fact that a single classifier cannot be generally efficient against all face regions, a two tier ensemble classifier based 3D face recognition approach is presented which employs Principal Component Analysis (PCA) for feature extraction and Mahalanobis Cosine (MahCos) matching score for classification of facial regions with weighted Borda Count (WBC) based combination and a re-ranking stage. The performance of proposed approach is corroborated by extensive experiments performed on two databases: GavabDB and FRGC v2.0, confirming effectiveness of fusion strategies to improve performance. | 3D face recognition based on pose and expression invariant alignment |
S0045790615002128 | Mobility currently evolves far beyond owning a car or using public transit services. Passenger transport can be managed by mobility providers by combining and extending various mobility services either directly or by using available mobility service platforms. This paper evaluates the capabilities and technical features of existing mobility service platforms with a special focus on electric mobility. Based upon this evaluation, criteria are presented which future platforms should address. As part of this work, a marketplace approach is developed which addresses the identified criteria. Potential marketplace architectures are presented which are deemed to establish marketplace interconnectivity. The developed marketplace approach and the proposed architectures contribute to the vision of an interconnected service ecosystem for mobility services. | The potential of interconnected service marketplaces for future mobility |
S0045790615002153 | Street lighting is a ubiquitous utility, but sustaining its operation presents a heavy financial and environmental burden. Many schemes have been proposed which selectively dim lights to improve energy efficiency, but little consideration has been given to the usefulness of the resultant street lighting system. This paper proposes a real-time adaptive lighting scheme, which detects the presence of vehicles and pedestrians and dynamically adjusts their brightness to the optimal level. This improves the energy efficiency of street lighting and its usefulness; a streetlight utility model is presented to evaluate this. The proposed scheme is simulated using an environment modelling a road network, its users, and a networked communication system – and considers a real streetlight topology from a residential area. The proposed scheme achieves similar or improved utility to existing schemes, while consuming as little as 1–2% of the energy required by conventional and state-of-the-art techniques. | A traffic-aware street lighting scheme for Smart Cities using autonomous networked sensors |
S0045790615002189 | This paper presents a new particle swarm optimization (PSO) algorithm, called the PSO-IAC algorithm, to resolve the goal of reaching with the obstacle avoidance problem for a 6-DOF manipulator of the home service robot. The proposed PSO-IAC algorithm integrates the improved adaptive inertia weight and the constriction factor with the standard PSO. Both the free-space and obstacle avoidance states are established for evaluations in computer simulations and real-time experiments. The performance comparisons of the PSO-IAC algorithm with respect to the existing inertia weighted PSO (PSO-W), constriction factor based PSO (PSO-C), constriction factor and inertia weighted PSO (PSO-CW), and adaptive inertia weighted PSO (PSO-A) algorithms are examined. Simulation results indicate that the PSO-IAC algorithm provides the fastest convergence capability. Finally, the proposed control scheme can make the manipulator of the home service robot arrive at the goal position with and without obstacles in all real-time experiments. | Integrated particle swarm optimization algorithm based obstacle avoidance control design for home service robot |
S0045790615002207 | Wireless sensor networks may be used for the surveillance of large systems (bridges, tunnels, etc.) or in the management of disasters such as forest fires, or oil spills. In some of these applications, the topology of the network is going to be dynamic: a connected system can evolve into a clustered system that presents a break of the global connectivity. Using a collector which will regularly visit the disjoint clusters enables to restore a discreet connectivity. A session layer protocol is proposed to reconstitute a consistent global information system. It enables the collector to reconstruct the communication context with the previously visited clusters, knowing they could have moved, merged, or have split. A node sensor model has been integrated into the Riverbed Opnet Modeler network simulation environment. Simulations show the benefits of the protocol, and particularly how it provides a better trajectory planning of the collector. | A session protocol for wireless sensor networks. Application to oil spills monitoring |
S0045790615002220 | This paper proposes a cross-layer mobility support scheme for the IPv6 over low-power wireless personal area network (6LoWPAN) wireless sensor network (WSN). This scheme combines the handover in the network layer (L3) with the handover in the link layer (L2) so that the L3 handover and the L2 one can be performed simultaneously. During the L3 handover process, a sensor node neither needs a care-of address nor participates in the handover process. During the L2 handover process, a node uses the channel information to directly achieve the L2 handover without scanning all channels. Finally, this paper analyzes and evaluates the performance of this protocol, and the data results show that this protocol improves the mobility handover performance. | A cross-layer mobility support protocol for wireless sensor networks |
S0045790615002244 | The existing clustering algorithms are either static or dynamic depending on the frequency of clustering. In static clustering, clusters are formed once, which reduces the clustering overhead but leads to early energy drain of a few nodes in the network. The network lifetime can be improved by dynamic clustering in which clusters are reformed after every round, which increases the clustering overhead. To optimize the parameters, including clustering overhead, network lifetime, energy hole, FND (first node dies) and LND (last node dies) in WSN, a hybrid unequal clustering with layering protocol (HUCL) is proposed. The HUCL is a hybrid of static and dynamic clustering approaches. In HUCL, the network is divided into layers and clusters of various sizes. The cluster heads are selected based on available energy, the distance to the sink and the number of neighbors. Once the cluster is formed, the same structure is maintained for a few rounds. The data are forwarded to the sink through a multi-hop layer-based communication with an in-network data compression algorithm. In comparison with the existing protocols, the HUCL balances energy and achieves a good distribution of clusters, extends the lifetime of the network and avoid the energy hole problem. | Energy efficient data collection through hybrid unequal clustering for wireless sensor networks |
S0045790615002256 | Preclinical micro-computed tomography (microCT) images are of utility for 3D morphological bone evaluation, which is of great interest in cancer detection and treatment development. This work introduces a compression strategy for microCTs that allocates specific substances in different Volumes of Interest (VoIs). The allocation procedure is conducted by the Hounsfield scale. The VoIs are coded independently and then grouped in a single DICOM-compliant file. The proposed method permits the use of different codecs, identifies and transmit data corresponding to a particular substance in the compressed domain without decoding the volume(s), and allows the computation of the 3D morphometry without needing to store or transmit the whole image. The proposed approach reduces the transmitted data in more than 90% when the 3D morphometry evaluation is performed in high density and low density bone. This work can be easily extended to other imaging modalities and applications that work with the Hounsfield scale. | Efficient storage of microCT data preserving bone morphometry assessment |
S0045790615002268 | In real-time collaborative environments, address space transformation strategy can be used to achieve consistency maintenance of shared documents. However, as for the execution of compound operations, they are firstly decomposed into primitive operations, the relationships between the referencing objects and referenced objects are lost during the decomposition process. Besides, the Undo operations in this environment are targeted at compound operations, but not decomposed basic ones. However, the traditional algorithms take primitive operation as the manipulation unit, thus leading to semantic inconsistencies of compound Undo operations. This paper appends two history buffers to maintain the relationships between the original operations and the decomposed ones and introduces “Retrace-Undo-VT-Redo-Retrace” strategy to realize the consistency maintenance of compound operations. Also, this paper introduces the version-decomposition strategy, describes the main algorithms of the compound Undo operations and analyses the validity of the strategy. Case analysis is given to show the effectiveness of the strategy. | Consistency maintenance of compound operations in real-time collaborative environments |
S0045790615002281 | This paper proposes an unambiguous correlation function applicable to generic sine-phased binary offset carrier (BOC) signal tracking. In the proposed scheme, first, we view the BOC sub-carrier pulse as a sum of multiple rectangular pulses. Then, we obtain partial correlation functions by correlating the multiple rectangular pulses with the received signal, and subsequently, construct two symmetric correlation functions by combining the partial correlation functions in a specialized way. Finally, we generate an unambiguous correlation function by combining the two symmetric correlation functions. The proposed correlation function has a sharper main-peak, and consequently, provides a better tracking performance than those of the conventional correlation functions in terms of the tracking error standard deviation (TESD). | An unambiguous correlation function for generic sine-phased binary offset carrier signal tracking |
S0045790615002311 | In this paper a dynamic modeling, simulation, control and energy management of photovoltaic water-pumping network system is presented. A fuzzy-logic controller has been proposed for a real-time control of the system. The controller generates the reference speeds needed for the pulse-width-modulation generator to control each DC/DC boost converter taking into account the water levels in three tanks and the instantaneous value of the solar radiation. The main objectives of the fuzzy-logic controller are the design of an adequate maximum power-point tracker to extract the maximum power, regulate the water in the three tanks and finally ensure the correct operation for all the conversion strings in order to optimize the quantity of pumped water. The system performance under different scenarios has been checked carrying out Matlab/Simulink simulations using a practical load-demand profile and real weather data and comparing them to another control algorithm. photovoltaic panel ideal factor normal operating cell temperature rated voltage short-circuit current temperature coefficient of ISC constant of proportionality between G and Iph photocurrent PVP output voltage optimal values V electronic charge Boltzmann’s constant cell temperature PVP shunt resistance optimal values of I reference of solar radiation temperature coefficient stator voltage stator current stator inductance rotor resistance mutual inductance mechanical speed of the machine electromagnetic torque reference speed of motor i level of tank I output flow of tank I DC link capacity band-gap energy maximum power rated current serial cells open circuit voltage parallel cells solar radiation PVP output current ideality factors cell-reverse-saturation current reverse-saturation current PV array-series resistance cell-reference temperature DC link voltage DC link capacity saturation current for Tr rotor voltage rotor current rotor inductance stator resistance coefficient of friction total inertia of the machine load torque duty cycle of DC inverter i input flow of pump i DC link voltage | A real-time control of photovoltaic water-pumping network |
S0045790615002335 | In this paper, we address the problem of broadcast routing and scheduling of video streaming for delay-sensitive applications in backbone wireless mesh networks. Given a source node and a set of destinations, we aim to build a broadcast tree and compute an optimal schedule such that the throughput for the source to broadcast streaming data to all the destinations is maximized. We divide the whole period for video broadcast into identical time frames and prove that maximizing the throughput can be converted into minimizing the length of a time frame. We propose a three-step method as a solution. Firstly, we build the broadcast tree by defining a new routing metric to select relay nodes. Then we use local search method to adjust the tree structure. Last, we propose a greedy method to schedule concurrent transmissions. Simulations have demonstrated that our method can improve the performance significantly compared with existing methods. | Throughput improvement for delay-sensitive video broadcast in wireless mesh networks |
S0045790615002359 | To enhance confidentiality and reduce the number of arrayed-waveguide grating (AWG) routers, a dynamic scrambling scheme is proposed in which cyclic and free spectral range (FSR) properties of AWG routers are employed to use a maximal-length sequence (M-sequence) code as the signature address code. In this paper, a changing codeword mechanism is presented in which a flexible dynamic scrambling algorithm is embedded in the encoding and decoding codebook to control the state of both the wavelength and spatial optical (or electrical) switch matrices. Hence, the code family and code changing flexibility of the proposed scheme increases substantially because of the multiple effects of the wavelength and spatial switch matrices. Compared with the existing dynamic reconfigurable AWG-based schemes without multiple changing codewords in the FSR groups and spatial domains, the confidentiality of the proposed scheme is approximately 104 times higher than that of schemes without scrambling codeword mechanisms. | Dynamic scrambling scheme of arrayed-waveguide grating-based encryptors and decryptors for protection against eavesdropping |
S0045790615002372 | This work investigates the digit serial polynomial basis multipliers performing multiplication in multiple binary extension fields F 2 m 1 , F 2 m 2 , … , F 2 m λ . Designing such versatile multipliers encounters a number of difficulties. First of all, the element sizes of the supported fields are different from each other, and thus the elements are represented with different number of bits for each field. To deal with different sized elements, designs with left or right justified operands are investigated. Secondly, each field multiplication involves modular reduction with a different irreducible polynomial, and thus the complexity can increase rapidly with the number of supported fields λ . To prevent this, two methods are studied: Using sparse irreducible polynomials and unifying the modular reduction computation of the fields by choosing the irreducible polynomials suitably. Our work shows that multiple fields can be supported at the cost of an O ( λ ) increase in area and an O ( λ ) increase in time. | Versatile digit serial multipliers for binary extension fields |
S0045790615002384 | Stealthy attackers move patiently through computer networks – taking days, weeks or months to accomplish their objectives in order to avoid detection. As networks scale up in size and speed, monitoring for such attack attempts is increasingly a challenge. This paper presents an efficient monitoring technique for stealthy attacks. It investigates the feasibility of proposed method under number of different test cases and examines how design of the network affects the detection. A methodological way for tracing anonymous stealthy activities to their approximate sources is also presented. The Bayesian fusion along with traffic sampling is employed as a data reduction method. The proposed method has the ability to monitor stealthy activities using 10–20% size sampling rates without degrading the quality of detection. | Detecting stealthy attacks: Efficient monitoring of suspicious activities on computer networks |
S0045790615002633 | The multifaceted nature of cyber-physical systems needs holistic study methods to detect essential aspects and interrelations among physical and cyber components. Like the systems themselves, security threats feature both cyber and physical elements. Although to apply divide et impera approaches helps handling system complexity, to consider just one aspect at a time does not provide adequate risk awareness and hence does not allow to design the most appropriate countermeasures. To support this claim, in this paper we provide a joint application of two model-driven techniques for physical and cyber-security evaluation. We apply two UML profiles, namely SecAM (for cyber-security) and CIP_VAM (for physical security), in combination. In such a way, we demonstrate the synergy between both profiles and the need for their tighter integration in the context of a reference case study from the railway domain. | On synergies of cyber and physical security modelling in vulnerability assessment of railway systems |
S0045790615002669 | Computer systems are required to process data more rapidly than ever, due to recent software and internet technology developments. The server computers work continuously and provide services to many clients simultaneously, which results in greater heat production and high temperature that must be managed in order to avoid malfunction and failure of critical hardware. In this study, three cooling systems were used comparatively to examine the temperature and performance of the CPU and motherboard. The temperature characteristics and performance of the CPU were tested with a heat sink, water cooling system, and thermoelectric cooler. According to the test results, the thermoelectric cooling system has better cooling performance than the other two systems under continuous operating conditions. Additionally, the performance rating of the CPU was the best with a thermoelectric cooler under varying workloads. | Performance and cooling efficiency of thermoelectric modules on server central processing unit and Northbridge |
S0045790615002670 | Sparse Imputation (SI) is a relatively new method that reconstructs missing spectral components of noisy speech signal with the help of the sparse-based representation approaches. In this method, the redundancy of signal in the frequency domain helps to rebuild noisy spectral components from the remained reliable ones. On the other hand different parts of speech signal, despite time intervals between them, can be inherently similar to each other. In this paper, a major modification over the SI method is proposed that in addition to data redundancy property of speech signal in small regions, takes the advantages of its self-similarity nature over long intervals. By identifying mostly similar frames, using a method based on the marginal classification, the Joint Sparsity method is applied and a method dubbed as the Joint Sparse Imputation is presented. The experiments conducted on AURORA 2 data set show that the proposed method significantly improves the recognition results in different noisy conditions, compared to the original SI method. | Joint Sparsity and marginal classification for improving Sparse Imputation performance in speech recognition |
S0045790615002694 | In this paper we use and extend a parallel optoelectronic processor for image preprocessing and implement software tools for testing and evaluating the presented algorithms. After briefly introducing the processor and showing how images can be stored in it, we adapt a number of local image preprocessing algorithms for smoothing, edge detection, and corner detection, such that they can be executed on the processor in parallel. These algorithms are performed on all pixels of the input image in parallel and, as a result, in steps independent of its dimensions. We also develop a compiler and a simulator for evaluating and verifying the correctness of our implementations. | Image preprocessing with a parallel optoelectronic processor |
S0045790615002700 | In general, in order for individuals to take part in a lottery, they must purchase physical lottery tickets from a store. However, due to the popularity and portability of smart phones, this paper proposes a lottery entry purchase protocol for joint multi-participants in a mobile environment. This method integrates cryptology, including elliptic curve cryptography and public key infrastructure, enabling users to safely and fairly join a lottery via a mobile device. The lottery organization involves an untraceable tamperproof decryptor to generate the winning numbers, and the generation of those winning numbers is fair and publicly verifiable. All participants share an equal probability of winning the prize. Subsequently, a comparison table shows that the proposed protocol can withstand attacks and efficiently satisfy the known requirements in a mobile environment. In addition, this study also ensures public verification and mutual authentication. | A novel lottery protocol for mobile environments |
S0045790615002712 | Recent technological trends such as cloud computing, wireless communication, and wireless sensor networks provide a strong infrastructure and offer a true enabler for health information technology services over the Internet. This system is based on the cloud computing environment, integrating mobile communication technology, context-aware technology, and wireless sensor networks to build a mobile web for a personalized health information service, which includes two health information recommendation service functions: a collaborative recommender and a physiological indicator-based recommender. We further propose a hybrid predictive model, which combines the Grey Theory and Markov chain to predict the moving object’s path. This will decrease the cost which arises from tracking errors and prolong the network’s lifetime. From the experiment results of usability, it has been discovered that subjects have positive responses towards usability measurement dimensions of the system: satisfaction, expectation-confirmation, perceived trust, perceived usefulness, and perceived value. | Design and evaluation of a cloud-based Mobile Health Information Recommendation system on wireless sensor networks |
S0045790615002724 | The emerging IEEE 802.22-based Wireless Regional Area Network (WRAN) is the first wireless standard based on the Cognitive Radio (CR) technology. WRAN is designed to offer wireless access services in a large coverage area by allowing Secondary Users (SUs) to opportunistically exploit the under-utilized licensed portion of spectrum that is primarily allocated for TV services. To enable efficient WRAN communications, the operation of a WRAN system should address two types of coexistence problem: incumbent co-existence and self-coexistence. In this paper, we investigate the self-coexistence problem in a multi-cell WRAN system that adopts an exclusive spectrum sharing policy. Specifically, we present an adaptive channel allocation scheme based on a cooperative max–min weighted fair allocation strategy. The proposed scheme is based on a centralized sensing mechanism that identifies the available spectrum opportunities for the WRAN cells. Our scheme dynamically allocates the available spectrum (idle channels) to the WRAN cells based on their expected traffic loads such that the total number of simultaneously admitted SU transmissions in the WRAN system is maximized. The expected traffic load is accurately estimated using a sample mean estimator based on previously monitored traffic in each cell. Simulation results indicate that our scheme is quite robust to traffic estimation error. Compared to reference spectrum allocation schemes, simulation results indicate that the proposed scheme effectively exploits the available spectrum opportunities by increasing the total number of served SU transmissions, which consequently results in a significant enhancement in the overall WRAN system performance. | Cooperative weighted-fair control strategy for spectrum self-coexistence in multi-cell WRAN systems |
S0045790615002736 | This paper studies sectorization increase in horizontal and vertical plane. We have simulated downlink (DL) macro long-term evolution (LTE) network using three-dimensional antenna and propagation models. New network layouts have been proposed based on 4-sector site deployment. The challenge was to offer lower network cost and complexity. Simulation results have showed good tradeoff between capacity and mobility performance in comparison to known sectorization schemes. Besides, carrier aggregation (CA) and active antenna system (AAS) have been used to exploit the sector vertical plane. Low frequency band (800MHz) improves coverage and indoor signal penetration in urban environment. Our proposed sectorization schemes give multi-objective network quality of service (QOS). | Novel radio cellular design improving capacity and mobility performance for advanced cellular networks |
S0045790615002748 | The increasing demand of cloud computing motivates the researchers to make cloud environment more efficient for its users and more profitable for the providers. Though virtualization technology helps to increase the resource utilization, still the operational cost of cloud gradually increases mainly due to the consumption of large amount of electrical energy. So to reduce the energy consumption virtual machines (VM) are dynamically consolidated to lesser number of physical machines (PMs) by live VM migration technique. But this may cause SLA violation and the provider is penalized. So to maintain an energy-performance trade-off, the number of VM migration should be minimized. VM migration primarily takes place in two cases: for hotspot mitigation and to switch off the underutilized nodes by migrating all its VMs. If a host is found to be overloaded then instead of immediately migrating some of its VMs we can check whether the migration is really required or not. For this we have proposed a load prediction algorithm to decide whether the migration will be performed or not. After the decision has been taken the algorithm finds a suitable destination host where the VM will be shifted. For this we have proposed a novel approach to decide whether a particular host is suitable as destination depending on its probable future load. We have simulated our algorithms in CloudSim using real world workload traces and compared them with the existing benchmark algorithms. Results show that the proposed methods significantly reduce the number of VM migration and subsequent energy consumption while maintaining the SLA. | Use of proactive and reactive hotspot detection technique to reduce the number of virtual machine migration and energy consumption in cloud data center |
S0045790615002761 | Wireless sensor networks (WSNs) have a wide range of applications in our lifetime. Indeed, WSNs perform a various missions and tasks in odor localization, firefighting, medical service, surveillance and security. In order to accomplish these tasks, the sensors have to perform partitioning protocols to form an organization into clusters and cliques. The hierarchical clustering is the key solution for WSNs to deal with the scalability problems in a network composed of millions of nodes. In this paper, a new hierarchical partitioning scheme is presented, named MCCC. It is cliques and clusters based hierarchical scheme that takes into account the size of cliques and clusters, it also minimizes the number of hops between the cluster head and its nodes. The proposed scheme is motivated by the need to have minimum and maximum size for cliques and clusters. This hierarchical scheme is proposed to respond to the energy and memory constraints for WSNs. | A multi-level clustering scheme based on cliques and clusters for wireless sensor networks |
S0045790615002785 | Data centers use dynamic virtual machine consolidation to reduce power consumption. Existing consolidation mechanisms are not efficient in cloud data centers, which have heterogeneous hardware infrastructure, huge scale, and highly variable non-stationary workloads. We use game theory to develop a novel distributed mechanism for both heterogeneous and homogeneous data centers of cloud computing. Our mathematical analysis shows that our mechanism converges after a finite number of migrations. In addition, we show that our worst case power consumption is only 23% more than the theoretical minimum. In order to validate our claim, we preform simulation in CloudSim with real workload traces from Google data centers. | Distributed consolidation of virtual machines for power efficiency in heterogeneous cloud data centers |
S0045790615002797 | Typical MAC protocols for IEEE 802.11-based ad hoc networks employ a direct transmission strategy whenever the transmitter can directly reach the receiver (one-hop transmission). While such a design enjoys simplicity, it limits the number of admitted transmissions in a given neighborhood. Due to the performance anomaly of 802.11-based wireless networks, transmission with low data rates occupy the shared medium for longer periods of time. Occupying the transmission medium for a longer period of time results in less available transmission time for other nodes, which consequently reduces the number of transmitted packets during the same period of time, leading to a reduction in network throughput. To improve the overall network throughput, we present a cooperative multi-channel MAC protocol for single-hop wireless mobile ad hoc networks that attempts at computing the path with the minimum required transmission time for a given source–destination pair (including the channel assignment along that path). The proposed protocol attempts at improving network performance by means of cooperative communications. According to our approach, if the one-hop (direct) path between communicating nodes supports low data rate (requires longer transmission time), the source selects a multi-hop path to the destination such that the total amount of required transmission time is minimized. Through simulations, we show that our proposed protocol achieves significant throughput and fairness improvement compared to the standard IEEE 802.11-based protocol. | Cooperative packet-forwarding mechanism for throughput improvement in multi-channel wireless networks |
S0045790615002803 | Efficient data delivery accompanied with low end-to-end delay is important in vehicular ad-hoc networks and optimal route selection is vital to improve these performance metrics. Different routing algorithms are proposed in VANETs. This paper reviews and analyzes these algorithms briefly and based on the analysis, a new opportunistic-based routing algorithm (OSTD) is proposed for urban scenarios. The proposed algorithm severely considers the type of vehicular distribution in the calculation of utility function. This utility function is used to evaluate the routes in the network. The reason of such a severe consideration is expressed and evaluated in the paper. Vehicle's driving path predictability is also used in the algorithm to forward the packet to a more suitable next hop, as vehicular mobility is the reflection of human social activity. Simulation results show that OSTD achieves a higher delivery ratio and lower end-to-end delay and packet loss compared to the other well-known protocols. | An opportunistic routing based on symmetrical traffic distribution in vehicular networks |
S0045790615002815 | Parallelization of task is considered to be a huge challenge for future extreme-scale computing system. Sophisticated parallel computing system necessitates solving the bus contention in a most efficient manner with high computation rate. The major challenge to deal with is the achievement of high CPU core usage through increased task parallelism by keeping moderate bus bandwidth allocation. In order to tackle the aforesaid problems, a novel arbitration technique, known as Parallel Adaptive Arbitration (PAA) has been proposed for the masters designed according to the traffic behaviour of the data flow. These masters are implemented using a synthetic benchmark program that measures sustainable memory bandwidth and the corresponding computational rate. The proposed arbitration technique is a strong case in favour of fair bandwidth optimization and high CPU utilization, as it consumes the processor cores up to 77% through high degree of task parallelization and also reduces bandwidth fluctuation. Some of the works published so far in this area are reviewed, classified according to their objectives and presented in an organised manner with a conclusion. | Design and simulation of a parallel adaptive arbiter for maximum CPU utilization using multi-core processors |
S0045790615002827 | This paper introduces a new fast integer-based algorithm to convert the RGB color representation to HSV and vice versa. The proposed algorithm is as accurate as the classical real-valued one. The use of only integer operations increases performance and portability. Performance measurement results show a speed gain of about two times when compared with the classical C++ language implementation on PC platforms. Lookup tables are not involved, thus the memory usage is minimal. The resulting HSV color can be packed into 48 bits. The proposed method can safely replace the commonly used floating-point implementation. | Integer-based accurate conversion between RGB and HSV color spaces |
S0045790615002839 | Broadcasting is the simplest form of communication in which nodes disseminate the same information simultaneously to all of their neighbors. Broadcasting has been widely used in many types of networks including wireless networks, wireless sensor networks, and mobile ad-hoc networks. Likewise these networks, broadcasting is also used in cognitive radio networks (CRNs) to accomplish various tasks such as spectrum sensing, spectrum sharing, spectrum management, and spectrum mobility. This article investigates and provides a comprehensive overview of various broadcasting strategies that have been proposed so far for cognitive radio networks. Moreover, it provides a detailed study of broadcast storm problem in CRNs. Finally, it discusses issues, challenges and future research directions for broadcasting strategies in CRNs. | Broadcasting strategies for cognitive radio networks: Taxonomy, issues, and open challenges |
S0045790615002840 | A number of mobile payment studies have been proposed in recently years. Most of the schemes are largely focused on transaction security, not on users’ privacy. In this paper, we propose an Unlinkable Anonymous Payment Scheme to provide a secure and anonymous mobile commerce environment. In the proposed protocol, a user applies an anonymous virtual credit card from a trusted service manager. The sensitive information of the applied credit card is stored in the secure elements of user’s mobile device. Our proposed protocol ensures various imperative security properties such as anonymity, unlinkability, and non-repudiation etc. | An Unlinkable Anonymous Payment Scheme based on near field communication |
S0045790615002876 | Current Critical Infrastructures (CIs) need intelligent automatic active reaction mechanisms to protect their critical processes against cyber attacks or system anomalies, and avoid the disruptive consequences of cascading failures between interdependent and interconnected systems. In this paper we study the Intrusion Detection, Prevention and Response Systems (IDPRS) that can offer this type of protection mechanisms, their constituting elements and their applicability to critical contexts. We design a methodological framework determining the essential elements present in the IDPRS, while evaluating each of their sub-components in terms of adequacy for critical contexts. We review the different types of active and passive countermeasures available, categorizing them and assessing whether or not they are suitable for Critical Infrastructure Protection (CIP). Through our study we look at different reaction systems and learn from them how to better create IDPRS solutions for CIP. | Awareness and reaction strategies for critical infrastructure protection |
S0045790615002979 | Foreign fibers in cotton seriously affect the quality of cotton products. Online detection systems of foreign fibers based on machine vision are the efficient tools to minimize the harmful effects of foreign fibers. The optimum feature set with small size and high accuracy can efficiently improve the performance of online detection systems. To find the optimal feature sets, a two-stage feature selection algorithm combining IG (Information Gain) approach and BPSO (Binary Particle Swarm Optimization) is proposed for foreign fiber data. In the first stage, IG approach is used to filter noisy features, and the BPSO uses the classifier accuracy as a fitness function to select the highly discriminating features in the second stage. The proposed algorithm is tested on foreign fiber dataset. The experimental results show that the proposed algorithm can efficiently find the feature subsets with smaller size and higher accuracy than other algorithms. | A two-stage feature selection method with its application |
S0045790615002980 | Variational decomposition has been widely used in image denoising, however, it can’t distinguish texture from noise well. Replacing the fixed parameter in the (BV, G) decomposition with a monotone increasing sequence, and iteratively taking the residual of the previous step as the input to decompose, we propose a multiscale variational decomposition model in this paper. Unlike the fixed-scale decomposition, the new model can decompose the input image into a sum of a series of features with different scales. So, texture can be distinguished from noise. In addition, we prove the nontrivial property and the convergence of this multiscale decomposition, and introduce a hybrid iteration algorithm that combines the first-order primal–dual algorithm with the gradient decent method to numerically solve the multiscale decomposition model. Numerical results validate the effectiveness of the proposed model. Furthermore, we apply this multiscale decomposition for image hierarchical restoration. Compared with the classical hierarchical (BV, L 2) decomposition, hierarchical wavelet decomposition and fixed-scale (BV, G) decomposition, our model has better performance for both synthetic and real images in terms of PSNR and MSSIM. | Multiscale variational decomposition and its application for image hierarchical restoration |
S0045790615002992 | The traditional approach for energy detection (ED) consists in the comparison of the energy received against a fixed detection threshold, estimated according to an expected noise level. However, the noise power is not a static parameter since it varies as a function of the random sources of noise and interference present in the network. This random nature of the noise power originates the so-called noise uncertainty problem which adversely affects the performance of the ED. In this paper, we propose and evaluate by means of computer simulation an adaptive energy detector that incorporates a noise power estimation strategy for adjusting the detection threshold according to the noise power present at each sensing epoch. As it can be proved by simulation results, our strategy helps in reducing the sensing errors and to improve the ED's sensitivity by alleviating the negative effects of the noise uncertainty. | Adaptive energy detector for spectrum sensing in cognitive radio networks |
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