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International Journal of Sensor Networks

 

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International Journal of Sensor Networks (33 papers in press)

 

Regular Issues

 

  • Recent Advances in Wireless Sensor Networks with Environmental Energy Harvesting
    by Lei Shu, Wanjiun Liao, Jaime Lloret, Lei Wang 
    Keywords: .

  • Energy Efficient Data Collection in Periodic Sensor Networks Using Spatio-Temporal Node Correlation   Order a copy of this article
    by Hassan Harb, Abdallah Makhoul, Ali Jaber, Samar Tawbi 
    Abstract: In wireless sensor networks (WSNs), the densely deployment and the dynamic phenomenon provide strong correlation between sensor nodes. This correlation is typically spatio-temporal. This paper proposes an efficient data collection technique, based on spatio-temporal correlation between sensor data, aiming to extend the network lifetime in periodic WSN applications. In the first step, our technique proposes a new model based on an adapted version of Euclidean distance which searches, in addition to the spatial correlation, the temporal correlation between neighboring nodes. Based on this correlation and in a second step, a subset of sensors are selected for collecting and transmitting data based on a sleep/active algorithm. Our proposed technique is validated via experiments on real sensor data readings. Compared to other existing techniques, the results show the effectiveness of our technique in terms of reducing energy consumption and extending network lifetime while maintaining the coverage of the monitored area.
    Keywords: Periodic Sensor Networks (PSNs); Spatio-Temporal Data Correlation; Sleep/Active Sensors; Real Data Readings.

  • Node Placement Approaches for Pipelines Monitoring: Simulation and Experimental Analysis   Order a copy of this article
    by Abdullatif Albaseer, Uthman Baroudi 
    Abstract: Monitoring oil, gas and water pipeline networks is a critical problem; its impact has serious consequences on the ecosystem. This problem has attracted, and for long time, the attention of industry and academia. One of the challenges in the pipeline monitoring process is how to optimally place the sensors that monitor the pipeline, detect and report any anomaly. Naturally, the deployed sensors are placed in a linear topology. This linear topology requires careful attention in placing sensors to ensure robustness against anomaly, minimize the energy consumption and maximize the network lifetime. In this work, we have studied two existing greedy node placement approaches via simulation and experimental analysis. First, we have validated experimentally the 31 power levels of CC2420 TelosB chipon and their corresponding transmission ranges. Having more power-level resolution provides more flexible power assignment, which yields less energy consumption and longer lifetime compared to traditional 8 power levels. Second, Extensive simulation and real experiments have been conducted. The results demonstrate a considerable drop in power consumption which can reach 73% and 23% extension in the network lifetime when all 31 power levels are adopted.
    Keywords: Leak detection; Wireless Sensor Network; Pipeline Monitoring; Equal-Power Placement; TelosB; Linear Node placement; Reliability; On-line monitoring.

  • A Profile Based Data Segmentation for In-Home Activity Recognition   Order a copy of this article
    by Mohammed AL Zamil, Rania AL Nadi 
    Abstract: A major problem in smart-home activity recognition is the ambiguity of interpreting the actions that formulate activities in smart home environments. Such ambiguity resulted from the redundancy of irrelevant actions and the concurrent interleaving among activities themselves. In this paper, we present a framework to minimize the effect of such ambiguity using profile based data segmentation and actions refinement. The proposed methodology relies on defining a profile for each sensor in the environment for the purpose of enriching existing features with semantic ones. Furthermore, according to these profiles, irrelevant actions within data segments are removed. Moreover, the proposed methodology addresses the connectivity among actions and their designated activities for the purpose of resolving interleaving among them. Experiments have been conducted to measure the performance of the proposed framework on a well-known datasets in this domain. We evaluated our methodology using three different classifiers: J48 (decision tree), Na
    Keywords: Internet of Things (IoT); Smart Home; Activity Recognition; Data Segmentation; Data Mining; Sensor Profile.

  • An Improved MDS Localization Algorithm for a WSN in a Sub-Surface Mine   Order a copy of this article
    by Heng Xu, Qiyue Li, Jianping Wang, Keqiong Chen, Wei Sun 
    Abstract: Wireless sensor networks (WSNs) have been successfully applied in a wide range of application domains. However, because of the properties of wireless signals, WSN applications in underground environments have been limited. In this paper, we present a Kalman-filter-based localization algorithm for use in a WSN deployed in a sub-surface mine for environmental monitoring to identify the positions of a large number of miners, each carrying a wireless mobile node. To improve the positioning accuracy even when current data are not available, we enhance the estimates of the Received Signal Strength Indication signal intensity and range obtained from the Kalman filter by adjusting them using the elastic particle model. Then, we obtain the distance matrix of the WSN based on AoA and the cosine theorem. Finally, we determine the final positions of all mobile nodes using a multidimensional scaling (MDS) algorithm.
    Keywords: Wireless Sensor Networks; Mobile Nodes; Localization; Sub-surface Mine; Kalman Filter; Elastic Particle Model; Angle of Arrival; Multidimensional Scaling Algorithm; No Line of Sight; Clustering.

  • Self-Stopping Strategies for Tractable Information Dissemination in Dense Mobile Sensor Networks   Order a copy of this article
    by Chao Chen, Zesheng Chen 
    Abstract: Epidemic routing is a simple forwarding mechanism and considered useful for wireless mobile sensor networks where infrastructure support is limited and sensed information has to be disseminated in a timely manner. The relaying overhead of epidemic routing, however, needs to be reduced to conserve energy. In this paper, we study a new problem in epidemic routing in wireless mobile sensor networks: what is a good strategy to timely stop message forwarding when a certain percentage of nodes have received a copy? The goal of such a strategy is to disseminate the information to a certain percentage of nodes in the network in a timely and predictable manner, and at the same time to suppress further spreading when the goal has been reached. As a first attempt, we focus on dense sensor networks where nodes move rapidly and randomly around and a synchronous time model is applied. We first select an accurate mathematical model to characterize the information dissemination in wireless mobile sensor networks. We then apply and extend the model to analyze and design different distributed self-stopping strategies. The probability-based self-stopping strategy adjusts the stopping probability to subdue the message forwarding when a sensor node meets a neighbor that is already informed. Such a strategy can reach the percentage goal accurately, but it does not stop timely and cannot control the information dissemination to a smaller scale than 82% of the network size. Using the message life time as a basic guideline, we propose two new self-stopping strategies by either setting a hop count limit or adopting a final forwarding probability. Such self-stopping strategies not only stop fast and save energy, but also are able to control the scope of message spreading to an arbitrary preset goal. We further test the self-stopping epidemic routing strategies in an emulated network with random waypoint mobility. We then present guidelines of selecting self-stopping strategies for tractable information dissemination based on different application requirements.
    Keywords: Epidemic routing; self-stopping strategies; mobile sensor networks.

  • ICRA: Index based Cache Replacement Algorithm for Cloud Storage   Order a copy of this article
    by Yuwei Zhao, Tinghuai Ma 
    Abstract: Meteorological data set is usually big and has a clear eld or some otherrncharacteristics. Moreover, it is mainly in the form of text. Each read and display will take up more system resources. In addition, the loading speed of the web page also affects the user's online experience to some extent. Based on these problems, this paper designs a storage mechanism for the original document and page data content using index and caching index. We proposed a cache replacement algorithm combined with indexing algorithm called Index Cache Replacement Algorithm. The main innovation of this paper is that we create index while reading the document and the page data at first time and analyze, sort, and cache the indexing data at the same time. When users browse the samerndocument or the page, we can directly index file to query and return the corresponding data to reduce the document reading time and page loading time. Thus, it enhances the effectiveness of cached data, increases the eciency of the cache query and improves the query file and byte hit rate which finally improving the performance of the network.
    Keywords: Meteorological data; Documents; Pages; Cache replacement algorithms;rnIndexes; Queries.

  • An Extensible Framework for ECG Anomaly Detection in Wireless Body Sensor Monitoring Systems   Order a copy of this article
    by Le Sun, Jinyuan He 
    Abstract: The wireless body sensor monitoring system is becoming more and more important in both academic and industry area. Wearing a number of body sensors enables a real time health monitoring, especially for the heart disease monitoring and detection. Automatic anomaly detection from the sensor streams of the Electrocardiography requires online techniques of data stream processing and analysis. The significant increase in the availability of the Electrocardiography collected from wireless sensor networks has attracted heaps of research interests and attempts in identifying the anomalies in an Electrocardiography. However, most existing models focus on a particular type of anomaly, like arrhythmia, and they are not dynamically extensible for the identification of an unknown type of anomaly. This work proposes an extensible method named shapelet-base (SH-BASE) to solve this problem. Essentially, SH-BASE is a knowledge-base of shapelets, in which the shapelets are classified into different groups (we call them branches), and each branch stores the most distinctive shapelets of a particular type of anomaly. Experimental results show that the SH-BASE can achieve a very competitive performance in anomaly detection for Electrocardiography sensor streams by comparing with the state-of-the-art models.
    Keywords: ECG; data streams; sensor networks; pseudo-periodic time-series; anomaly detection.

  • Urbihoc: A Delay Tolerant Approach for Data Acquisition in Urban Areas using a Mobile Wireless Sensor Network   Order a copy of this article
    by Martha Montes De Oca, Javier Gomez, Miguel Lopez Guerrero 
    Abstract: In recent years several pieces of research have proposed the use of wireless mobile nodes to sense a wide diversity of phenomena in urban areas. Data collected by mobile sensors are typically sent to a central server in order to be shared with other users through cellular or WiFi networks. Unfortunately, the cost of deploying and maintaining such infrastructure may be prohibitively high. Furthermore, a disaster situation on the server side may cause the failure of the whole system. As an alternative approach, in this work we introduce Urbihoc, a data acquisition method that uses opportunistic trans- missions to directly share data among mobile nodes. In this way, from local exchanges, Urbihoc builds up global knowledge about a monitored phenomenon. Our results sug- gest that, in some applications, it is possible to monitor a phenomenon over a large metropolitan area by using only the resources contributed by mobile users.
    Keywords: Wireless sensors networks; mobile crowdsensing; energy saving; urban sensing; delay tolerant approach.

  • WSN-aided Haze Pollution Governance: Modeling Public Willingness Based on Structural Equations   Order a copy of this article
    by Jibo Chen, Yingxi Song, Guizhi Wang, Qi Liu 
    Abstract: In recent decades, Wireless Sensor Networks have been well investigated and developed, and been widely used in environmental surveillance, climate data collection, meteorological prediction, etc. However, research activities on statistical analysis and decision making aided by Wireless Sensor Networks, especially in the area of environmental hazards and risk governance, are rarely presented. In this paper, common factors are extracted from exploratory factor analysis based on closed questionnaire data in this study. The optimal model of the haze governance willingness among the common factors is designed according to the Structural Equation Modeling, and then the relationships between in the influencing factors of public haze governance willingness are analyzed. The results show that haze governance and willingness will be affected by haze risk perception, perception quality, perception measures and economic expenditure factors, and the most important influential factors are the degree of physical damage, and the willing to take measures to prevent haze and improve rescuing operations. The impact of haze on life, the inconvenience of haze to trip, the maximum duration of haze, and the times suffering from haze are the most basic factors affecting the haze governance willingness. In order to achieve the governance of haze, the public desires the government to take firm measures to govern the haze (e.g. via a Wireless Sensor Network-based measurement network), with the collaboration from the public governance.
    Keywords: Haze Pollution; Wireless Sensor Networks-aided Measurement; Structural Equation Modeling; Haze Governance Willingness; Policy Suggestions.

  • A Cooperative Spectrum Sensing Method Based on Signal Decomposition and K-medoids Algorithm   Order a copy of this article
    by Yonghua Wang, Shunchao Zhang, Yongwei Zhang, Pin Wan, Shikun Wang 
    Abstract: In order to solve the problem of low sensing performance and low accuracy of threshold estimation in traditional spectrum sensing systems with low signal-to-noise ratio, we proposes a cooperative spectrum sensing method based on empirical mode decomposition and K-medoids clustering algorithm. At the same time, in order to improve the effectiveness of K-medoids clustering algorithm and improve the sensing performance of the system in the case of fewer collaborative secondary users, a feature extraction method based on empirical mode decomposition algorithm and matrix decomposition and recombination is proposed. The method can accurately acquire the characteristic information of the sampled signal and improve the feature accuracy. The method firstly uses the empirical mode decomposition algorithm to process the spectrum signal, reduce the noise components in the signal, and then extract the signal features using a matrix split and recombination method. Finally, the features are classified using the K-medoids clustering algorithm. In the experimental part, we verify the performance of the method under different signal-to-noise ratio. The experimental result shows that the method can effectively improve the sensing performance of the spectrum sensing system at low signal-to-noise ratio.
    Keywords: Spectrum sensing; Decomposition and recombination; K-medoids clustering algorithm; Feature extraction.

  • Spiderweb Strategy: Application for Area Coverage with Mobile Sensor Nodes in 3D Wireless Sensor Network   Order a copy of this article
    by BOUALEM Adda, DAHMANI Youcef, D.E. RUNZ Cyril, AYAIDA Marwane 
    Abstract: The problem of area coverage in 3D wireless sensor networks is a NP-Hard problem; the approaches used to optimize this problem are not effective because of the difficulty of ensuring 3D connectivity, communication,rnand monitoring. The fundamental problem of all these constraints is the difficulty of deploying the sensor nodes with fair densities on the 3D areas, in order to guarantee connectivity and coverage over all the network. In this paper, well take advantage of spider canvas. Indeed, spider web are made to catch insects, have fortes of strength and resilience remarkable. The mobility of the sensor nodes according to Archimedes spiral function facilitates the proper node positioning.rnPositioning the mobile sensor nodes by miming a spider canvas in 3D ensuresrnthe equitable distribution of nodes in the area of interest, as well; the ability to vary communication and surveillance radii makes ensuring connectivity and the entire coverage. We have make some simulations to assess performance of our algorithms. Our simulation show that the spider canvas strategy outperforms the area coverage in 3D scheme in both effectiveness and efficiency strategy.
    Keywords: Area Coverage; 3D WSN; Spiderweb Strategy; Efficient-Energy; Spiral Archimedes.

  • Average Distance Estimation in Randomly Deployed Wireless Sensor Networks (WSNs): An Analytical Study   Order a copy of this article
    by Cüneyt Sevgi 
    Abstract: A Wireless Sensor Network (WSN) is an energy-scarce network in which the energy is primarily dissipated by the sensor nodes during data transmission to the base station (BS). The location of the BS in a WSN dramatically affects the energy dissipation, the throughput, and the lifetime. While in a number of studies the optimal positioning of a BS is considered, the system parameters are optimized when the BS location is known in advance in many others. In this paper, we provide a general-purpose mathematical framework to find the expected distance value between every point within any n-sided simple polygon shaped sensing field and an arbitrarily located BS. Having the knowledge of this value is very imperative particularly in random deployment as it is used for energy-efficient clustering. Although similar derivations appear in the related literature, to the best of our knowledge, this study departs from them, since our derivations do not depend on the shape of the sensing field and the orientation of BS relative to it.
    Keywords: WSNs; wireless sensor networks; average distance; estimation; random deployment; base station.

  • A New Path Planning Strategy of a Data Collection Problem Utilizing Multi-mobile Nodes in Wireless Sensor Networks   Order a copy of this article
    by Ye Miao, Chou Hongbing, Wang Mei, Wang Yong, Feng Hao 
    Abstract: The prevalent research on the path planning problem in mobile node-based data collection techniques only considers the simple situation involving a single mobile node or path endpoint located at the centre of the communication. This paper considers additional situations involving both of the above two factors and abstracts from these scenarios to formulate a hybrid optimization problem. This optimization problem has the characteristics of high dimensionality and a large search space. To solve this problem, the following modifications were made. First, k sub-paths based on the k-SPLITOUR algorithm were obtained. Second, a method to eliminate path intersections was designed to optimize the discrete components. Finally, a hybrid glowworm swarm optimization algorithm (HGSO) was proposed to optimize the positions of access points along the communication circle to optimize the continuous components. The global convergence analysis of the proposed HGSO algorithm is given. Simulations and comparisons with other algorithms verified that the proposed strategy can solve the path planning problem in data collection utilizing multi-mobile nodes effectively.
    Keywords: Wireless Sensor Networks; Multi-mobile Nodes; Travelling Salesman Problem with Neighbourhoods (TSPN); Hybrid Glowworm Swarm Optimization (HGSO) Algorithm.

  • Spatial-Temporal Variability of PM2.5 Concentration in Xuzhou based on Satellite Remote Sensing and Meteorological data   Order a copy of this article
    by Xi Kan, Linglong Zhu, Yonghong Zhang, Yuan Yuan 
    Abstract: Accurate estimation of the spatiotemporally continuous distribution of PM2.5 concentration is of great significance for the research on atmospheric pollution. Previous studies have used satellite-derived AOD and meteorological parameters to estimate the PM2.5 concentration successfully. However, the effect of aerosol characteristics such as aerosol types was seldom considered in PM2.5 estimation model. In this manuscript, authors applied an aerosol classification-based method to generate ground-level PM2.5 concentration datasets in Xuzhou from 2014 to 2017. The coefficient of determination (R2) of aerosol classification-based model increases from 0.57 to 0.61 verified by ground station measurements, comparing to the empirical model. The results of spatiotemporal analysis show that the PM2.5 concentration has a slowly decreased trend in last three years, despite has an extreme high value in the winter of 2016 due to the heavy haze pollution occurred in Xuzhou. The diurnal variations of PM2.5 concentration displays a typically single peak mode, with the highest peak observed in the morning (7:00-11:00) and the lowest occurring at dusk (15:00-18:00). With regard to the spatial distribution of estimated PM2.5 over Xuzhou, there is a high-PM2.5 area anchoring over the urban district, while low concentration occurs in county town. Thus, the PM2.5 concentration has the high correlation with weather change and anthropogenic activities.
    Keywords: PM2.5; AOD; Satellite remote sensing; Aerosol classification; Spatial-Temporal Variation.

  • A Portable Roadside Vehicle Detection System Based on Multi-sensing Fusion   Order a copy of this article
    by Jianying Zheng, Bin Xu, Xiang Wang, Xueliang Fan, Hao Xu, Guang Sun 
    Abstract: In order to solve traffic congestion problem and improve traffic efficiency, the intelligent transportation system is widely used in urban roads. The sensing system is preferred to be deployed at roadside to detect vehicles in the adjacent lane. The advantage is that the normal traffic wouldnt be interfered. In the field of the magnetic vehicle detection, one of the most challenging problems is that the disturbance from the other lane. Most existing magnetic detection systems need more than one magnetic sensor to solve the disturbance. However, these magnetic sensors need well designed and installed or these systems wouldnt work well. In this paper, we propose a portable roadside vehicle detection system based on multi-sensing fusion. Cooperated with the magnetic sensor and the ultrasonic sensor, the disturbance from non-detected lane can be excluded and the traffic volume of the detected lane can be calculated accurately. Through on-road experiments, the vehicle detection accuracy can achieve 97.14% in a two-lane road. The experimental results demonstrate that the proposed system in this paper can achieve high accuracy and the sensing system is able to be deployed at roadside in multilane roads to get traffic flow reliably.
    Keywords: Vehicle detection; magnetic sensor; ultrasonic sensor; multi-sensing fusion.

  • Energy Efficient Virtual Network Embedding for Wireless Multi-hop Cellular Networks Using Multi-commodity Flow Algorithm   Order a copy of this article
    by Yifei Wei, Li Li, Zihan Jia, Xiaojun Wang 
    Abstract: With the rapid development of wireless mobile communication technologies, the trend of generalization and centralization requires variable communication devices and flexible network structures. To improve the transmission quality and extend the cell coverage, multi-hop relay network, as a wireless access network, has become an important part of communication system framework. Furthermore, to support seamless communication of multiple devices and services in heterogeneous wireless networks with high resources utilization, network virtualization has been proposed to offer a flexible and scalable management. In this paper, we study the wireless multi-hop cellular network and the problem of virtual network embedding. We first analyze the wireless multi-hop cellular network scenario and establish a virtual network embedding model. After that we propose a minimum cost flow algorithm based on the multi-commodity flow algorithm. Thus the problem is transformed into a multi-commodity flow problem. We finally put forward an optimization algorithm of Lagrange relaxation and sub-gradient algorithm to solve the problem. The simulation results show that the proposed multi-commodity flow algorithm can make full use of network resources, and improve the acceptance rate of virtual network requests, so as to improve the quality of service.
    Keywords: Virtual network embedding; Multi-commodity flow algorithm; Multi-hop relay; Lagrangian relaxation.

  • DAO-R: Integrating Data Aggregation and Offloading in Sensor Networks Via Data Replication   Order a copy of this article
    by Basil Alhakami, Bin Tang, Jianchao Han, Mohsen Beheshti 
    Abstract: When sensor network applications are deployed in an inaccessible or inhospitable region, or under extreme weather, it is usually not viable to install a long-term base station in the field to collect data. The generated sensory data is therefore stored inside the network first, waiting to be uploaded. However, when more data is generated than available storage spaces in the entire network can possibly store, and uploading opportunities have not arrived, data loss becomes inevitable. We refer to this problem as {em overall storage overflow} in sensor networks. To overcome overall storage overflow, existing research designs a two-stage approach as below. First, by taking advantages of spatial correlation that commonly exists among sensory data, it aggregates overflow data to the size that can be accommodated by the available storage capacity in the network. Then, it offloads the aggregated data into the network to be stored. We refer to this naive two-stage approach as DAO-N. DAO-N is NP-hard. In this paper, we demonstrate that this approach does not necessarily achieve good performance in terms of energy consumption. We propose a more unified framework that is based upon data replication techniques in order to solve overall storage overflow and improve the performance of DAO-N. We refer to our approach as DAO-R. Specifically, we design two energy-efficient data replication algorithms to integrate data aggregation and data offloading seamlessly. We also give a sufficient condition under which DAO-R can be solved optimally. Via extensive simulations, we show that DAO-R outperforms DAO-N by around $30%$ in terms of energy consumption under different network parameters.
    Keywords: Data Aggregation; Data Offloading; Overall Storage Overflow; Sensor Networks; Algorithms; Energy-Efficiency.

  • A theoretical investigation on moving average filtering solution for fixed-path map matching of noisy position data   Order a copy of this article
    by Baris Baykant Alagoz 
    Abstract: Precisely estimation of moving object locations from position sensors promises useful implications for many fields of engineering. The mapping of a moving object on a predefined path is an important process for object tracking and remote control applications. Due to measurement noises of sensors and uncertainties, the measured object location may not precisely match to paths or roads in a map. This study presents a numerical method for a low computational-complexity solution of point to arc type mapping problems. This method has two main tasks: a noise reduction task by short-time moving average filtering of noisy two-dimensional position data, and a map matching task to estimate exact position of an object on a map. To evaluate performance of the investigated method, the algorithm is applied for bus route tracking simulations and results are discussed for several road scenarios and various levels of noise.
    Keywords: Map matching; noisy position data; short-time moving average filtering; point to arc mapping; object tracking.

  • Development of a Wireless Intravenous Drip Rate Monitoring Device   Order a copy of this article
    by Pratyush Kumar Patnaik, Suraj Kumar Nayak, Anilesh Dey, Sirsendu Sekhar Ray, Kunal Pal 
    Abstract: Biotelemetry increases the efficiency of the healthcare professionals. This study proposes the development of a wireless communication-enabled low-cost, automated drip rate monitoring system, used for intravenous (IV) therapy. The proposed system monitors the falling fluid drops inside the drip chamber, and subsequently calculates and displays the drip rate on a Liquid crystal display (LCD) panel. It is capable of wirelessly notifying the central monitoring station when the drip rate is outside the set range. The system was designed using a light emitting diode (LED), a light dependent resistor (LDR), a microcontroller and a Xbee wireless module. The proposed device is simple, user-friendly and can reduce the workload of the healthcare givers by reducing their regular visit to the patient site.
    Keywords: Drip Rate; Intravenous Infusion; LED; LDR; Microcontroller; Arduino Uno; Zigbee; Wireless Network; Mesh Topology; Graphical User Interface.

  • A New Optimization Model and Algorithm for Virtual Optical Networks   Order a copy of this article
    by Shanshan Hao, Yuping Wang, Beicong Lv 
    Abstract: Virtual Optical Network is considered to be the next generation internet architecture and is of big value. Currently, it has many issues to be solved, e.g., node mapping, link mapping and spectrum assignment. More and more challenges will be faced when there are privileged nodes through which certain connection requests can not pass in the physical topology. To solve the above issues, this paper put forward a new optimization model in virtual optical network considering privileged nodes, and aims to minimize the maximum index of used frequency slots. A routing algorithm is designed for the model, an adaptive strategy is put forward to determine the crossover rate and mutation rate, whats more, a new crossover and mutation operator are proposed. Based on these, a novel genetic algorithm is proposed to solve the problem. To evaluate the efficiency of the model and the algorithm, numerous experiments are conducted on four widely used network topologies. Simulation results show the feasibility of the model and the effectiveness of the algorithm.
    Keywords: Network Scheduling; Optimization Model; Virtual Optical Network; Genetic Algorithm.

  • A Mixed-Coding Adaptive Differential Evolution for Optimizing the Architecture and Parameters of Feedforward Neural Networks   Order a copy of this article
    by Li Zhang, Hong Li 
    Abstract: This paper presents an adaptive differential evolution with mixed-coding strategy to evolve feedforward neural networks (FNNs). This algorithm with adaptive control parameters which can handle effectively binary variables and real variables, is used to optimize simultaneously FNN architecture and connection parameters (weights and biases) by a specific individual representation and evolutionary scheme. The performance of the algorithm has been evaluated on several benchmarks. The results demonstrate that the proposed algorithm can produce compact FNNs with good generalization ability.
    Keywords: Feedforward Neural Network; Evolutionary Neural Network; Differential Evolution; Generalization Ability.

  • Maximization of the number of $beta$-view covered targets in visual sensor networks   Order a copy of this article
    by Ling Guo, Deying Li, Yongcai Wang, Zhao Zhang, Guangmo Tong, Weili Wu, Dingzhu Du 
    Abstract: In some applications using visual sensor networks, the facing directions of targets are bounded. Existing full-view coverage (all the facing directions of a target constitutes a disk) is not necessary. Therefore, a novel model called $beta$-view coverage, where only necessary facing directions of a target are effectively viewed, is proposed but uses much fewer cameras than those used by full-view coverage model.rnrnBased on this new model, a new problem called $beta$-view covered Target Maximization (BVCTM) problem is proposed to maximize the number of $beta$-view covered targets given some fixed and freely rotatable camera sensors. The NP-hardness of this problem is proven. We transform BVCTM problem into an Integer Linear Programming problem equivalently. Thereafter, a $displaystyle{(1-e^{-1})}$-factor approximate algorithm and a camera-utility based greedy algorithm are given to it. Finally, we conduct many experiments and investigate the influence of many parameters on these two algorithms.
    Keywords: Visual Sensor Networks; Target Coverage; $beta$ View Coverage.

  • Quality of Barrier Cover with Wireless Sensors   Order a copy of this article
    by Weili Wu, Zhao Zhang, Chuangen Gao, Hai Du, Hua Wang, Ding-Zhu Du 
    Abstract: A set of wireless sensors is called a barrier cover if they can monitor the boundary of an area so that an intruder cannot enter the area without being found by any sensor. The quality of a barrier cover is the shortest length of path along which an intruder can enter the area from outside. This shortest length is called the width of the barrier cover. Given a set of sensors, how to find the minimum subset of sensors which form a barrier cover with required width? How to find the maximum number of disjoint subsets of sensors, each form a barrier cover with required width? In this paper, we study these two problems. We introduce a concept of $w$-simple barrier cover, which is a barrier cover with width $w$, consisting of a sequence of sensors as shown in Fig.2. For $w$-simple barrier covers, we design polynomial-time algorithms for solving above two problems. In general, we show the NP-hardness of above two problems and design efficient heuristics to solve them; the performance of these heuristics are evaluated by computational experiments.
    Keywords: wireless sensor network; barrier cover; computational complexity; algorithm.

  • Partition-aware centrality measures for connectivity restoration in mobile sensor networks   Order a copy of this article
    by Izzet Fatih Senturk 
    Abstract: Mobile Sensor Networks (MSNs) often operate unattended in environments where human intervention is limited. To sustain network operations, network connectivity must be maintained at all times. However, the network can be partitioned due to random node failures. To tolerate such failures in a reactive manner, network topology can be restructured through node mobility. Minimizing the mobility cost requires addressing two different challenges. First, identifying nodes to be relocated. Second, determining target locations for movement. We address the first problem by presenting three different partition-aware centrality measures based on closeness centrality, geometric centrality, and harmonic centrality. To determine the movement target, we consider the former locations of the upstream nodes so that simultaneous node failures can be tolerated with limited data collection scope. The approaches that we present in this paper not only ensure recovery but also minimize the recovery cost so that the network lifetime is extended.
    Keywords: Mobile sensor networks; topology management; closeness centrality; geometric centrality; harmonic centrality; connectivity restoration; fault tolerance; mobility.

  • An intelligent monitoring system for a pig breeding environment based on a wireless sensor network   Order a copy of this article
    by Chong Chen, Xingqiao Liu 
    Abstract: The piggery environment is an important factor affecting health level, growth and development of pigs, which plays a decisive role in safe pork production. To facilitate environmental monitoring for large-scale pig farms, an environmental monitoring system of air quality parameters for livestock breeding is developed based on a wireless sensor network (WSN). The system could accomplish distributed measurement, data storage, and centralized management of air quality parameters such as temperature, humidity, ammonia and carbon dioxide, and could also automatically control the work of fan and wet curtain. As the piggery environment is a multi-variable, nonlinear and time-varying system, there are coupling effects among them. It is difficult to establish a precise mathematical model. Therefore, neural decoupling fuzzy control technology is employed. Fuzzy controllers are designed to control temperature and humidity, respectively. In order to reduce the coupling effect between them, a compensation decoupling controller is designed, which adjusts weight coeffients of neural networks and compensates for the effects of mutual coupling. Experimental results indicated that, compared with the data from an air quality analyzer, measurement
    Keywords: intelligent monitoring; environmental control; livestock breeding; WSN; wireless sensor network; fuzzy control; decoupling control.

  • An energy-saving wireless sensor network based model for monitoring of ammonia concentration   Order a copy of this article
    by Chong Chen, Xingqiao Liu, Chengyun Zhu 
    Abstract: The ammonia concentration in the piggery plays a key role in the growth of fattening pigs in livestock breeding. In this study, we propose an intelligent environmental monitoring system for piggery based on a wireless sensor network, which achieves multi-point, large-scale environmental monitoring in piggery. Specifically, a model has been developed to predict environmental parameters in the server. Due to the determining role of ammonia concentration on pig health, this model facilitates the determination of environmental control strategy and evaluation of environmental quality in piggery. To optimize its prediction accuracy, this model was designed based on least squares support vector regression (LSSVR) with chaotic mutation to improve the estimation of distribution algorithm (CMEDA) for searching of the optimized parameters, which are γ
    Keywords: energy-saving; prediction model; LSSVR; least squares support vector regression; chaotic mutation; EDA; estimation of distribution algorithm; WSN; wireless sensor network.

  • Enhancing Reliability by Adoptive Graph traversals for Backbone assisted Communication in Wireless Sensor Networks   Order a copy of this article
    by Itu Snigdh, Nisha Gupta 
    Abstract: Some applications in wireless sensor networks (WSN) require dedicated backbones for effective and faster delivery of data under the stringent network conditions. An inherent flaw of such networks is that with the failure of a relay node the entire structure is affected and needs restructuring in the worst case failures. In this article we try to enhance the capabilities of such type of networks in terms of reliability by providing spare routes for robust data delivery. Our approach is twofold. Firstly, we estimate the reliability of the network through Markov model to show the improvement and effect on the reliability due to employing ad hoc spare routes in the existing backbone structures. Secondly, we also propose and implement an adoptive relay selection algorithm (ARS) to confirm the improvement in the percentage of data delivery at the sink. Our analysis shows the improvement on the packet delivery ratio and the reliability under different failure conditions.
    Keywords: Wireless sensor network; communication reliability; Markov model; packet delivery ratio; Breadth First Search; Minimum spanning trees.

  • Computational model for the recognition of lower limb movement using wearable gyroscope sensor   Order a copy of this article
    by Tahir Hussain, Hafiz Farhan Maqbool, Nadeem Iqbal, Mukhtaj Khan, Salman ., Abbas Deghani Sanij 
    Abstract: Human activity recognition using inertial sensors, has enabled many applications in different fields, especially healthcare and biomedical engineering. In this regard, an activity recognition system is proposed using the signals of a single gyroscope sensor placed at the shank. Principal component analysis method was utilized to exclude the redundant features from the feature set. Furthermore, different classifiers such as probabilistic neural network, k-nearest neighbour and support vector machine were used for recognition walking activities. K-fold cross validation and four performance parameters namely accuracy, sensitivity, specificity, and Matthews correlation coefficient were used to inspect the performance of the recognition model. The proposed model yielded encouraging recognition accuracy 98.4 % compared to the existing activity recognition systems. It is realized that the proposed system will potentially be utilized in the control of lower limb prosthesis and be useful tool for the gait analysis applications.
    Keywords: principal component analysis; human activity recognition; gyroscope; support vector machine; classification.

  • Controlling Interferences in Smart Building IoT Networks using Machine Learning   Order a copy of this article
    by Per Lynggaard 
    Abstract: The coexistence of many IoT networks in smart buildings poses a major challenge because they interfere mutually. In most settings this results in a greedy approach where each IoT node optimizes its own performance parameters like increasing transmit-power, etc. However, this means that interference levels are increased, battery powers are wasted, and spectrum resources are exhausted in high dense settings. To control interference levels, share spectrum resources, and lower the overall power-consumptions this paper proposes a centralized control scheme which is based on a nonlinear cost function. This cost function is optimized by using machine learning in the form of a binary particle swarm optimization algorithm. It has been found that this approach shares the spectrum in a fair way, it saves power and lowers the interference levels, and it dynamically adapts to network changes.
    Keywords: Smart buildings; IoT networks; interferences; fading; machine learning; BPSO; transmit power regulation; centralized control scheme.

  • Dynamic Load Tuning for Energy-Hole Avoidance in Corona Model for a Wireless Sensor Network   Order a copy of this article
    by Krishna Pal Sharma, T.P. Sharma 
    Abstract: In wireless sensor networks, communication load varies from region to region. Nodes near to sink communicate more than nodes at farther away from sink. This load imbalance causes an energy hole around sink and affects overall network lifetime. Therefore, an approach is proposed to enhance networks lifetime by balancing energy depletion rate across network and avoiding energy hole around sink. The approach is based on corona model for wireless sensor networks to balance energy depletion in inter-corona as well as in intra-corona. Initially, we prove that in a corona model the energy depletion rate across coronas can be sub-balanced by assigning communication ranges in decreasing order from outermost corona towards innermost corona. Thereafter, we prove that if communication ranges are assigned in decreasing order to coronas from outermost towards innermost for a non-uniformly deployed network with increasing density towards sink, balanced energy depletion can be achieved by deploying lesser number of nodes as compared to a non-uniformly deployed network with fixed and uniform communication ranges. Additionally, relay load is tuned over the nodes during data transmission in order to balance intra-corona energy depletion rate of nodes with in a corona. The dynamic relay load tuning is done through a function of relay load and remaining energy of nodes. The proposed scheme can be used for networks with both uniform and non-uniform nodes deployment. In order to validate the results, the approach is compared with baseline approaches through ns-2 based simulation.
    Keywords: Communication range; Energy holes; Network lifetime; Non-uniform deployment; Wireless Sensor Networks.

  • Information and Communication Technologies for the improvement of the Irrigation Scheduling   Order a copy of this article
    by Mohamed Ali Fourati, Walid Chebbi, Mounir Ben Ayed, Anas Kamoun 
    Abstract: Nowadays, agricultural water management is becoming a disturbing issue where scarce resources are increasingly affected by global warming and economic current changes. Indeed, actual irrigation systems are not perfectly adjusted to real contexts or they do not support farmers to carry out all their activities and needs. In order to redress existent deficiencies, information and communication technologies (ICT) are well proposed to minimize losses and improve decisions against unforeseen water shortages. We present in this work a precision irrigation application based on wireless and decision support technologies. Our application provides real-time remote control of decisions and optimizes allocation of exactly required water quantities (beginning and stopping, interruption and recovery times). The objective of such an application is to facilitate the manipulation of the irrigation process and offer flexible opportunities for better watering scheduling and reserves distribution. Therefore, efficient yield will be raised and better profits in time and money will be achieved. We had developed and deployed the system in a real case study where results are evaluated and well judged as regards the objectives.
    Keywords: Precision irrigation; information and communication technologies; wireless sensors network; decision support system; optimization; remote control.

  • Data Retrieval for Deadline-based Multi-request in MIMO Wireless Networks   Order a copy of this article
    by Ping He, Weidong Li, Shufu Cao 
    Abstract: Data retrieval problem is an important issue that generates an access pattern for downloading a request with multiple data items among the parallel channels such that the efficiency of wireless networks is improved. Although many related papers have discussed data retrieval problem that clients require to retrieve one request under the condition of clients equipped with one and multiple antennae, but there are few study on this problem that clients equipped with multiple antennae require to retrieve multiple requests, in particular that each request has time constraint. The problem has great value in the aspects of theory and applications in MIMO wireless networks, such as data sharing and e-business. So, this paper proposes an algorithm that schedules the suitable antennae to find a retrieval sequence (to access data items) about these requests for keeping the balance of access latency among the antennae. For retrieving each request, we develop an efficient scheme that adopts maximum match to generate an access pattern for downloading all requested data items so that the access latency of each request and deadline miss ratio are minimized. Through experiments, the proposed algorithms keep good performance.
    Keywords: Mobile computing; Data broadcast; Indexing; Data scheduling; Datarnretrieval; Data grouping.