Search

An accurate localization algorithm tailored for anisotropic wireless sensors networks (WSNs) is proposed in this paper. Using the proposed algorithm, each regular or position-unaware node estimates its distances only to reliable anchors or position-aware nodes. The latter are properly chosen following a new reliable anchor selection strategy that ensures an accurate distance estimation making thereby our localization algorithm more precise. It is shown that the proposed algorithm is implementable in both 2-dimensional (2D) and 3-dimensional (3D) scenarios. A power saving mechanism aiming to enhance the WSN lifetime is also envisaged in this paper. It is proven that the proposed algorithm could easily incorporate such a mechanism. Simulations show that our algorithm, whether combined or not with the power saving mechanism, consistently outperforms the best representative localization algorithms currently available in the literature in terms of accuracy, even with the presence of nonuniform node distribution or radiation irregularities. [ABSTRACT FROM AUTHOR]

This paper deals with the problem of group behavior recognition. Our approach is to merge all the possible features of group behavior (individuals, groups, relationships between individuals, relationships between groups, etc.) with static context information relating to particular domains. All this information is represented as a set of features by classification algorithms. This is a very high-dimensional problem, with which classification algorithms are unable cope. For this reason, this paper also presents four feature selection alternatives: two wrappers and two filters. We present and compare the results of each method in the basketball domain. [ABSTRACT FROM AUTHOR]

This paper addresses the localization of a timing signal source based on the time of arrival (TOA) measurements that are collected from nearby sensors that are position known and synchronized to each other. Generally speaking, for such TOA-based source localization, the corresponding observation equations contain nonlinear relationship between measurements and unknown parameters, which normally results in the nonexistence of any efficient unbiased estimator that attains the Cramer-Rao lower bound (CRLB). In this paper, we devise a new approach that utilizes linearization and adopts suitable coordinate system translation to eliminate nonlinearity from the converted observation equations. The performance analysis and simulation study conducted show that our proposed algorithm can achieve the CRLB when the zero-mean Gaussian and independent measurement errors are sufficiently small. [ABSTRACT FROM AUTHOR]

This paper considers the localization problem in mobile sensor networks. Such a problem is a challenging task, especially when measurements exchanged between sensors may contain outliers, that is, data not matching the observation model. This paper proposes two algorithms robust to outliers. These algorithms perform a set-membership estimation, where only the maximal number of outliers is required to be known. Using these algorithms, estimates consist of sets of boxes whose union surely contains the correct location of the sensor, provided that the considered hypotheses are satisfied. This paper proposes as well a technique for evaluating the number of outliers to be robust to. In order to corroborate the efficiency of both algorithms, a comparison of their performances is performed in simulations using Matlab. [ABSTRACT FROM AUTHOR]

Power assignment in wireless ad hoc networks is an important issue of topology control which assigns power for each wireless node so that the induced communication graph satisfies some desired properties such as the connectivity and the energy spanner. In this paper, we study the problem of power assignment in order that its induced communication graph meets the following properties: (1) it is an energy-t-spanner which is energy efficient; (2) it is k-fault resistant which can withstand up to k - 1 node failures where k⩾1; (3) the interference is minimal. We propose algorithms to address this problem. Both the theoretic analysis and the simulations in the paper prove that our algorithms can induce a k-fault resistant energy spanner and furthermore the interference is minimized. To the best of our knowledge, this is the first paper to study the power assignment problem simultaneously considering spanner properties, the fault tolerance, and the interference reduction. [ABSTRACT FROM AUTHOR]

Wireless sensor networks (WSNs) are tightly linked with the practical environment in which the sensors are deployed. Sensor positioning is a pivotal part of main location-dependent applications that utilize sensornets. The global topology of the network is important to both sensor network applications and the implementation of networking functionalities. This paper studies the topology discovery with an emphasis on boundary recognition in a sensor network. A large mass of sensor nodes are supposed to scatter in a geometric region, with nearby nodes communicating with each other directly. This paper is thus designed to detect the holes in the topological architecture of sensornets only by connectivity information. Existent edges determination methods hold the high costs as assumptions. Without the help of a large amount of uniformly deployed seed nodes, those schemes fail in anisotropic WSNs with possible holes. To address this issue, we propose a solution, named PPA based on Poincare-Perelman Theorem, to judge whether there are holes in WSNs-monitored areas. Our solution can properly detect holes on the topological surfaces and connect them into meaningful boundary cycles. The judging method has also been rigorously proved to be appropriate for continuous geometric domains as well as discrete domains. Extensive simulations have been shown that the algorithm even enables networks with low density to produce good results. [ABSTRACT FROM AUTHOR]

A wireless sensor network (WSN) model by analyzing the limitations of existing localization algorithm is proposed in this paper. Specifically, neither the anchor nor the ID is required in the proposed model, and the node function is limited. The hardware function of the node in our model is independent of the MAC protocol. Moreover, based on the proposed WSN model, we design an energy efficient anchor-free localization algorithm for no-identity WSN. Instead of multiple measurements, mathematical calculation is adopted to acquire the position information. Subsequently, the effectiveness of the algorithm is confirmed by rigid theory. The simulation results show that the proposed algorithm can improve the performance of localization and energy efficiency in WSN significantly. [ABSTRACT FROM AUTHOR]

Backpressure based scheduling has revealed remarkable performance in wireless multihop networks as reported in a lot of previous work. However, its lack of consideration on energy use efficiency is still an obstacle for backpressure based algorithms to be deployed in resource-constrained wireless sensor networks (WSNs). In this paper, we focus on studying the design of energy efficient backpressure based algorithm. For this purpose, we propose a gradient-assisted energy-efficient backpressure scheduling algorithm (GRAPE) for WSNs. GRAPE introduces a new link-weight calculation method, based on which gradient information and nodal residual energy are taken into account when making decisions on backpressure based transmission scheduling. According to the decisions made by this new method, packets are encouraged to be forwarded to nodes with more residual energy. We theoretically prove the throughput-optimality of GRAPE. Simulation results demonstrate that GRAPE can achieve significant performance improvements in terms of energy use efficiency, network throughput, and packet delivery ratio as compared with existing work. [ABSTRACT FROM AUTHOR]

Gas source localization (GSL) is a critical component in wireless sensor network (WSN) which can be used to estimate the position of gas leaks through the gas concentration measured by the monitoring nodes. In this paper, we first derive a gas diffusion model under windy conditions based on the gas diffusion theory. Because of the nonlinearity of the gas diffusion model under windy conditions, the traditional weighted centroid algorithm for gas source localization produces very inaccurate estimation of the source location. To address this problem, we propose a novel gas source localization algorithm which combines the weighted centroid method and particle filter. Simulation results validate the effectiveness of our algorithm under unknown gas source strength. Compared to weighted centroid method alone, our algorithm shows a higher accuracy in location. Moreover, its convergence rate is improved by the preestimation of initial value. [ABSTRACT FROM AUTHOR]

This paper presents an opportunistic reception (OR) algorithm for energy-efficient transmission in cooperative wireless sensor networks (WSNs), where the characteristics of random linear network coding and the energy consumption property of WSNs are jointly considered. In OR, the sensor nodes in intermediate cluster generate the independent coding vector through simple forwarding or decoding-recoding manners opportunistically, so that the number of received packets can be reduced. To evaluate the algorithm, we derive the average number of received packets, the transmitting nodes, and decoding failure probability under specific assumption. The obtained theoretical and simulation results verify the effectiveness offered by the proposed approach. [ABSTRACT FROM AUTHOR]

Node localization is essential in wireless sensor networks (WSNs). However, due to limited node energy and overhead network, node localization faces many challenges in WSNs. In addition, it is difficult to meet the requirement of localization accuracy and energy consumption at the same time in existing algorithms. In this paper, we proposed a novel eliminating algorithm called NPLA which achieves high localization accuracy and reduces energy consumption effectively. It makes full use of multiple-hop neighbor nodes of unknown node to eliminate the possible location area (PLA) of the unknown node. Simulations show that the localization error of algorithm NPLA can be controlled within 20%. [ABSTRACT FROM AUTHOR]

Most applications of industrial wireless sensor networks (IWSNs) should converge process data generated by each node to the central manager. The data collection operation results in an important communication primitive referred to as convergecast. Convergecast is a many-to-one communication paradigm as a critical functionality deployed for industrial monitoring and control. Delaying of process data may degrade the overall control performance and even lead to the malfunction of industrial applications. Therefore, timeslot and channel resources should be scheduled efficiently for real-time communication. This paper is interested in determining a TDMA schedule that minimizes the number of timeslots and completes convergecast with a limited number of channels. In order to achieve the lower bound derived by theoretical analysis, we proposed a source aware scheduling algorithm for general network. For IWSNs with a fixed number of available channels, we present a source aware scheduling algorithm with constrained channel. According to simulation results, we demonstrate that the performance of our algorithm is close to the lower bound on latency with a limited number of channels. Our algorithm is also scalable for schedules with multiple packets and specific transmission latency of a single packet. [ABSTRACT FROM AUTHOR]

Due to the nonexistence of end-to-end path between the sender and the receiver in delay tolerant networks and mobile social networks, consequently successful message transmission faces great challenges. In this paper, an adaptive routing algorithm taking full use of gregariousness characteristics of moving nodes is proposed. We first abstract all social relationships and uniformly represent them using friendship. Then by dynamically dividing nodes into different social groups, we finish flooding message among the target social group where destination node resides. In addition, we propose a social group based flooding model and a message redundancy control model to select fewer but better relay nodes and further reduce message redundancy. Extensive simulations have been conducted based on the synthetic traces generated by working day movement model and the results show that the proposed routing algorithm can get a higher message delivery ratio and a lower overhead ratio compared to Bubble Rap, Epidemic, and ProPHET, thus proving a better routing performance. [ABSTRACT FROM AUTHOR]

Localization is a key issue for wireless sensor network. The traditional localization methods achieve high location accuracy using received signal strength (RSS) in line of sight (LOS) environment. But the localization accuracy degrades significantly in nonline of sight (NLOS) environment. So the localization in NLOS environment is one of the most challenging for wireless sensor network. In this paper, we propose an RSS based localization algorithm in NLOS environment. A NLOS identification algorithm is firstly proposed. This algorithm does not need the parameters of the NLOS in prior. Then we correct the NLOS measurements by subtracting the mean of NLOS errors. Finally, the Kalman filter is employed to mitigate the process noise. In simulations, we demonstrate that the proposed algorithm achieves higher localization accuracy compared with other methods. [ABSTRACT FROM AUTHOR]

In recent years, trust-aware routing protocol plays a vital role in security of wireless sensor networks (WSNs), which is one of the most popular network technologies for smart city. However, several key issues in conventional trust-aware routing protocols still remain to be solved, such as the compatibility of trust metric with QoS metrics and the control of overhead produced by trust evaluation procedure. This paper proposes a trust-aware secure routing framework (TSRF) with the characteristics of lightweight and high ability to resist various attacks. To meet the security requirements of routing protocols in WSNs, we first analyze features of common attacks on trust-aware routing schemes. Then, specific trust computation and trust derivation schemes are proposed based on analysis results. Finally, our design uses the combination of trust metric and QoS metrics as routing metrics to present an optimized routing algorithm. We show with the help of simulations that TSRF can achieve both intended security and high efficiency suitable for WSN-based networks. [ABSTRACT FROM AUTHOR]

Wireless sensor networks have been widely studied for decades. There are many research areas that have been explored such as service availability and energy efficiency. Load balancing is one of the key techniques which can be used to solve the tradeoff between the both sides. In this paper, we propose a novel real-time load balancing technique which does not require the knowledge of static traffic demands and is based on control theory. We first formulate the packet forwarding problem into a classic control model and then derive the controller model. Then, we propose an algorithm to implement the controller and perform the simulation. The simulation results show that, our algorithm can balance the network traffic in real time and decreases maximum link utilization (MLU) sharply. Our algorithm reduces MLU by 78.4% compared to the shortest path first (SPF) routing and by 53.8% compared to another packet scheduling algorithm which was proposed in a previous work. [ABSTRACT FROM AUTHOR]

A vector quantizer is a system for encoding the original data to reduce the bits needed for communication and storage saving while maintaining the necessary fidelity of the data. Signal processing over distributed network has received a lot of attention in recent years, due to the rapid development of sensor network. Gathering data to a central processing node is usually infeasible for sensor network due to limited communication resource and power. As a kind of data compression methods, vector quantization is an appealing technique for distributed network signal processing. In this paper, we develop two distributed vector quantization algorithms based on the Linde-Buzo-Gray (LBG) algorithm and the self-organization map (SOM). In our algorithms, each node processes the local data and transmits the local processing results to its neighbors. Each node then fuses the information from the neighbors. Our algorithms remarkably reduce the communication complexity compared with traditional algorithms processing all the distributed data in one central fusion node. Simulation results show that both of the proposed distributed algorithms have good performance. [ABSTRACT FROM AUTHOR]

Mobile localization using distributed sensor network has attracted significant research interest in recent years. One of the main challenges for mobile location estimation is the presence of the non-line-of-sight (NLOS) propagation. It results in erroneous measurements containing NLOS error due to the reflection and diffraction. The NLOS error could seriously reduce the localization accuracy. This paper presents a novel mobile localization method for distributed sensor network in NLOS propagation scenarios. The aim of the method is to mitigate the NLOS error and enhance the localization accuracy. The transition between the LOS and NLOS is described by two-state Markov model. The interacting multiple model frame is employed to estimate the position of unknown node. The probability data association algorithm is used to filter the estimated location. The simulation results show that the proposed method outperforms the traditional filter method in NLOS scenarios. [ABSTRACT FROM AUTHOR]

Clustering in vehicular ad hoc networks is an effective approach to make dynamic wireless vehicular sensor networks more manageable and stable. To make vehicle clustering applicable everywhere regardless of the provided infrastructure, vehicles must rely only on themselves and must not take any supporting services, such as location or external communication services, for granted. In this paper, we propose a new clustering metric and a clustering algorithm with multihoming support. It relies only on the vehicle's ability to send and receive wireless packets which identify the vehicle relationship. Clusters are created with redundant connections between nodes to increase the communication reliability in case of topological changes and the cluster creation process is also inverted compared to other algorithms. The presented solution is verified and compared to MOBIC with the use of ns-3 and SUMO simulation tools. Simulation results have confirmed the expected behavior and show that our algorithm achieves better node connectivity and cluster stability than the former. [ABSTRACT FROM AUTHOR]

The service- oriented architecture is considered as a new emerging trend for the future of wireless sensor networks in which different types of sensors can be deployed in the same area to support various service requirements. The accuracy of the sensed data is one of the key criterions because it is generally a noisy version of the physical phenomenon. In this paper, we study the node selection problem with data accuracy guarantee in service-oriented wireless sensor networks. We exploit the spatial correlation between the service data and aim at selecting minimum number of nodes to provide services with data accuracy guaranteed. Firstly, we have formulated this problem into an integer nonlinear programming problem to illustrate its NP-hard property. Secondarily, we have proposed two heuristic algorithms, namely, Separate Selection Algorithm (SSA) and Combined Selection Algorithm (CSA). The SSA is designed to select nodes for each service in a separate way, and the CSA is designed to select nodes according to their contribution increment. Finally, we compare the performance of the proposed algorithms with extended simulations. The results show that CSA has better performance compared with SSA. [ABSTRACT FROM AUTHOR]

This paper presents and puts forward an optimal automatic distributing of physical cell identity (ADPCI) scheme for the selforganizing network (SON). Considering the high number and the layered structure of the evolved node B (eNodeB, eNB) in the initial rollout phase, the assigning of PCI for cells would be quite complex. The PCI self-distributing problem is mapped to the well-known minimum spanning tree (MST) problem in order to optimize the PCI reuse distance and decrease the multiplexing interference. The correlation property of PCI is analyzed and taken into consideration in the assigning phase. Moreover, a suboptimal algorithm (SADPCI) is presented as it performs approximately to ADPCI but the computational complexity is lower. To demonstrate the proposal validity, performances of ADPCI and SADPCI are evaluated. Simulation results illustrate that these schemes can achieve significantly higher performance even under the condition of severe PCI deficiency. [ABSTRACT FROM AUTHOR]

There is a growing interest in the use of video sensor networks in surveillance applications in order to detect intruders with low cost. The essential concern of such networks is whether or not a specified target can pass or intrude the monitored region without being detected. This concern forms a serious challenge to wireless video sensor networks of weak computation and battery power. In this paper, our aim is to prolong the whole network lifetime while fulfilling the surveillance application needs. We present a novel scheduling algorithm where only a subset of video nodes contributes significantly to detect intruders and prevent malicious attacker to predict the behavior of the network prior to intrusion. Our approach is chaos based, where every node based on its last detection, a hash value and some pseudorandom numbers easily compute a decision function to go to sleep or active mode. We validate the efficiency of our approach through theoretical analysis and demonstrate the benefits of our scheduling algorithm by simulations. Results show that in addition to being able to increase the whole network lifetime and to present comparable results against random attacks (low stealth time), our scheme is also able to withstand malicious attacks due to its fully unpredictable behavior. [ABSTRACT FROM AUTHOR]

Coverage is one of the key issues to achieve energy efficiency of a wireless sensor network. Sensor scheduling is one of the most important methods to solve coverage problems. It can ensure the coverage degree of a region and prolong the network lifetime. In this paper, we focus on the k-coverage scheduling problem to guarantee k-coverage sensing and network connectivity. We consider both deterministic and stochastic sensing models of the sensors and adapt the results of deterministic sensing model to solve the sensor scheduling problem under the stochastic sensing model. We use regular pentagons to divide the sensing disks to solve the k-coverage problem. Each sensor node runs a stochastic k-coverage-preserving scheduling algorithm to determine its work modes, and redundant nodes can enter into sleep mode, while active nodes ensure the coverage of the network. Theoretical analysis and simulation results show that our algorithm can reduce the number of active nodes and extend the network lifetime significantly while maintaining a given coverage degree. [ABSTRACT FROM AUTHOR]

A large-scale deployment of femtocell BSs (FBSs) causes substantial energy consumption. This paper proposes a hybrid BS-cooperative power management (HBCPM) scheme with self-organized sleep mode in virtual cell-based femto networks. Firstly, HBCPM builds a leader-member virtual cell framework, in which only one FBS is a FBS leader (FL) and others are FBS members (FMs). Then, the FL acts as an autonomous entity and is responsible for detecting active calls in the virtual cell coverage, while the FMs without active connections can entirely shut down pilot transmissions and the related processing all the time. So it is suited for self-organizing networks (SONs). Based on the proposed scheme, the state transition model is established by the semi-Markov stochastic process, and the analytic formulas of average cumulative delay and interference time as well as the energy consumption are derived. Meanwhile, three prominent-related schemes are also studied by the proposed model. With the practical long-term evolution (LTE) system parameters and three-dimensional femtocell network model, the numerical simulation and theoretical analysis match pretty well, and the tradeoff between the energy consumption and average cumulative delay is also manifested. Moreover, simulation results show that the proposed algorithm outperforms other three schemes in terms of average cumulative interference time and the energy consumption. [ABSTRACT FROM AUTHOR]

This paper addresses the problem of the connectivity control and the self-organized deployment/dispersion of a team of mobile ad hoc sensor nodes. First, to reduce redundant communication links while preserving global connectivity, a distributed link removal algorithm is developed that only requires local information of no more than two-hop neighbors. Secondly, for the purpose of preserving essential links while avoiding collisions, a combined piecewise-continuous motion controller is designed to regulate the motion of mobile sensors between two consecutive switches. The proposed hybrid control system can autonomously disperse a team of mobile sensors towards their final configuration with guaranteed connectivity and collision avoidance. Theoretical analysis and computer simulations have confirmed the efficiency and scalability of the proposed schemes. [ABSTRACT FROM AUTHOR]

This paper presents a novel multicast routing protocol for wireless sensor networks, named Multicast tree protocol with Pruning and Energy Balancing (MPEB) to disseminate data through a layered multicast tree with high-efficiency and low-power consumption. With pruning algorithm and energy balancing algorithm, MPEB can save energy and balance load. Pruning algorithm records and maintains backup parents for each child node, and thus it can detach possible nodes from the multicast tree and turn as many nodes as possible to sleep. Energy balancing algorithm protects nodes with low power from running out of energy and dying out, and thus it can balance total energy consumption of the whole network and prolong the network lifetime. The formal validations and simulations evaluate the performance of MPEB, which shows that MPEB has a distinct advantage over others in both reducing and balancing energy consumption. [ABSTRACT FROM AUTHOR]

Source localization is an important problem in wireless sensor networks (WSNs). An exciting state-of-the-art algorithm for this problem is maximum likelihood (ML), which has sufficient spatial samples and consumes much energy. In this paper, an effective method based on compressed sensing (CS) is proposed for multiple source locations in received signal strength-wireless sensor networks (RSS-WSNs). This algorithm models unknown multiple source positions as a sparse vector by constructing redundant dictionaries. Thus, source parameters, such as source positions and energy, can be estimated by ϱ1-norm minimization. To speed up the algorithm, an effective construction of multiresolution dictionary is introduced. Furthermore, to improve the capacity of resolving two sources that are close to each other, the adaptive dictionary refinement and the optimization of the redundant dictionary arrangement (RDA) are utilized. Compared to ML methods, such as alternating projection, the CS algorithm can improve the resolution of multiple sources and reduce spatial samples of WSNs. The simulations results demonstrate the performance of this algorithm. [ABSTRACT FROM AUTHOR]

In order to reduce the location estimation error in wireless sensor network (WSN), a localization algorithm is proposed combining sliding-mode and spring-relaxation-like techniques for wireless sensor networks in this paper. Our proposed method takes advantage of the spring-relaxation technique. The overall accuracy of the location estimations is improved by sliding-mode technique. The convergence of the proposed algorithm is proved using the convergence conditions of discrete sliding-mode. Moreover, it requires only a few beacons with known locations to compute the location estimations of all sensors. Simulation examples demonstrate the overall accuracy of the proposed method. [ABSTRACT FROM AUTHOR]

Recent years have witnessed a growing interest in applications of wireless sensor and actor networks (WSANs). In WSANs, maintaining interactor connectivity is of vital concern in order to reach application level. Failure of a critical actormay partition the inter-actor network into disjoint segments. This paper proposed an application-oriented fault detection and recovery algorithm (AFDR), a novel distributed algorithm to reestablish connectivity. AFDR identifies critical actors and designates backups for them. A backup actor detects the critical node failure and initiates a recovery process via moving to the optimal position. The purpose of AFDR is to satisfy application requirements, reduce recovery overhead, and limit the impact of critical node failure on coverage and connectivity to the utmost. The effectiveness of AFDR is validated through simulation experiments. [ABSTRACT FROM AUTHOR]

Area coverage is one of the key issues for wireless sensor networks. It aims at selecting a minimum number of sensor nodes to cover the whole sensing region and maximizing the lifetime of the network. In this paper, we discuss the energy-efficient area coverage problem considering boundary effects in a new perspective, that is, transforming the area coverage problem to the target coverage problem and then achieving full area coverage by covering all the targets in the converted target coverage problem. Thus, the coverage of every point in the sensing region is transformed to the coverage of a fraction of targets. Two schemes for the converted target coverage are proposed, which can generate cover sets covering all the targets. The network constructed by sensor nodes in the cover set is proved to be connected. Compared with the previous algorithms, simulation results show that the proposed algorithm can prolong the lifetime of the network. [ABSTRACT FROM AUTHOR]

To mitigate the performance degradation induced by the cell outage, in this paper, a centralized cell outage compensation management mechanism and the corresponding work flow are proposed. Then a concrete algorithm named autonomic particle swarm compensation algorithm (APSCA) is proposed to generate the compensation scheme. The simulation results show that the proposed APSCA is effective to resolve the coverage problems induced by the outage. In the simulation scenario, almost 98.3% users that would otherwise be dropped will be served by the surrounding cells, and the block probabilities of the compensating cells are still kept on the accepted levels. [ABSTRACT FROM AUTHOR]