28,050 research outputs found

    On perimeter coverage in wireless sensor networks with minimum cost

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    One of the major applications of sensor networks is tracking and surveillance. Very often, a single sensor is sufficient to monitor a single target. However, when the object is very large, several sensors have to work together to monitor the object continuously. In this paper, we study how to identify a set of sensors that can cover the perimeter of a large target with the minimum cost. We develop a novel distributed algorithm that requires fewer messages than existing mechanisms. Our algorithm can be extended to solve the problem when the sensor range is adjustable. We provide a formal proof of correctness and convergence time analysis of our algorithm. We further demonstrate the performance through extensive simulations. © 2011 Inderscience Enterprises Ltd.postprin

    Achieving Minimum Coverage Breach under Bandwidth Constraints in Wireless Sensor Networks

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    This paper addresses the coverage breach problem in wireless sensor networks with limited bandwidths. In wireless sensor networks, sensor nodes are powered by batteries. To make efficient use of battery energy is critical to sensor network lifetimes. When targets are redundantly covered by multiple sensors, especially in stochastically deployed sensor networks, it is possible to save battery energy by organizing sensors into mutually exclusive subsets and alternatively activating only one subset at any time. Active nodes are responsible for sensing, computing and communicating. While the coverage of each subset is an important metric for sensor organization, the size of each subset also plays an important role in sensor network performance because when active sensors periodically send data to base stations, contention for channel access must be considered. The number of available channels imposes a limit on the cardinality of each subset. Coverage breach happens when a subset of sensors cannot completely cover all the targets. To make efficient use of both energy and bandwidth with a minimum coverage breach is the goal of sensor network design. This paper presents the minimum breach problem using a mathematical model, studies the computational complexity of the problem, and provides two approximate heuristics. Effects of increasing the number of channels and increasing the number of sensors on sensor network coverage are studied through numerical simulations. Overall, the simulation results reveal that when the number of sensors increases, network lifetimes can be improved without loss of network coverage if there is no bandwidth constraint; with bandwidth constraints, network lifetimes may be improved further at the cost of coverage breach

    Barrier Coverage in Wireless Sensor Networks

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    Barrier coverage is a critical issue in wireless sensor networks (WSNs) for security applications, which aims to detect intruders attempting to penetrate protected areas. However, it is difficult to achieve desired barrier coverage after initial random deployment of sensors because their locations cannot be controlled or predicted. In this dissertation, we explore how to leverage the mobility capacity of mobile sensors to improve the quality of barrier coverage. We first study the 1-barrier coverage formation problem in heterogeneous sensor networks and explore how to efficiently use different types of mobile sensors to form a barrier with pre-deployed different types of stationary sensors. We introduce a novel directional barrier graph model and prove that the minimum cost of mobile sensors required to form a barrier with stationary sensors is the length of the shortest path from the source node to the destination node on the graph. In addition, we formulate the problem of minimizing the cost of moving mobile sensors to fill in the gaps on the shortest path as a minimum cost bipartite assignment problem and solve it in polynomial time using the Hungarian algorithm. We further study the k-barrier coverage formation problem in sensor networks. We introduce a novel weighted barrier graph model and prove that determining the minimum number of mobile sensors required to form k-barrier coverage is related with but not equal to finding k vertex-disjoint paths with the minimum total length on the WBG. With this observation, we propose an optimal algorithm and a faster greedy algorithm to find the minimum number of mobile sensors required to form k-barrier coverage. Finally, we study the barrier coverage formation problem when sensors have location errors. We derive the minimum number of mobile sensors needed to fill in a gap with a guarantee when location errors exist and propose a progressive method for mobile sensor deployment. Furthermore, we propose a fault tolerant weighted barrier graph to find the minimum number of mobile sensors needed to form barrier coverage with a guarantee. Both analytical and experimental studies demonstrated the effectiveness of our proposed algorithms

    QoS Provision for Wireless Sensor Networks

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    Wireless sensor network is a fast growing area of research, receiving attention not only within the computer science and electrical engineering communities, but also in relation to network optimization, scheduling, risk and reliability analysis within industrial and system engineering. The availability of micro-sensors and low-power wireless communications will enable the deployment of densely distributed sensor/actuator networks. And an integration of such system plays critical roles in many facets of human life ranging from intelligent assistants in hospitals to manufacturing process, to rescue agents in large scale disaster response, to sensor networks tracking environment phenomena, and others. The sensor nodes will perform significant signal processing, computation, and network self-configuration to achieve scalable, secure, robust and long-lived networks. More specifically, sensor nodes will do local processing to reduce energy costs, and key exchanges to ensure robust communications. These requirements pose interesting challenges for networking research. The most important technical challenge arises from the development of an integrated system which is 1)energy efficient because the system must be long-lived and operate without manual intervention, 2)reliable for data communication and robust to attackers because information security and system robustness are important in sensitive applications, such as military. Based on the above challenges, this dissertation provides Quality of Service (QoS) implementation and evaluation for the wireless sensor networks. It includes the following 3 modules, 1) energy-efficient routing, 2) energy-efficient coverage, 3). communication security. Energy-efficient routing combines the features of minimum energy consumption routing protocols with minimum computational cost routing protocols. Energy-efficient coverage provides on-demand sensing and measurement. Information security needs a security key exchange scheme to ensure reliable and robust communication links. QoS evaluation metrics and results are presented based on the above requirements

    Energy Consumption Of Visual Sensor Networks: Impact Of Spatio-Temporal Coverage

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    Wireless visual sensor networks (VSNs) are expected to play a major role in future IEEE 802.15.4 personal area networks (PAN) under recently-established collision-free medium access control (MAC) protocols, such as the IEEE 802.15.4e-2012 MAC. In such environments, the VSN energy consumption is affected by the number of camera sensors deployed (spatial coverage), as well as the number of captured video frames out of which each node processes and transmits data (temporal coverage). In this paper, we explore this aspect for uniformly-formed VSNs, i.e., networks comprising identical wireless visual sensor nodes connected to a collection node via a balanced cluster-tree topology, with each node producing independent identically-distributed bitstream sizes after processing the video frames captured within each network activation interval. We derive analytic results for the energy-optimal spatio-temporal coverage parameters of such VSNs under a-priori known bounds for the number of frames to process per sensor and the number of nodes to deploy within each tier of the VSN. Our results are parametric to the probability density function characterizing the bitstream size produced by each node and the energy consumption rates of the system of interest. Experimental results reveal that our analytic results are always within 7% of the energy consumption measurements for a wide range of settings. In addition, results obtained via a multimedia subsystem show that the optimal spatio-temporal settings derived by the proposed framework allow for substantial reduction of energy consumption in comparison to ad-hoc settings. As such, our analytic modeling is useful for early-stage studies of possible VSN deployments under collision-free MAC protocols prior to costly and time-consuming experiments in the field.Comment: to appear in IEEE Transactions on Circuits and Systems for Video Technology, 201

    Coverage Protocols for Wireless Sensor Networks: Review and Future Directions

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    The coverage problem in wireless sensor networks (WSNs) can be generally defined as a measure of how effectively a network field is monitored by its sensor nodes. This problem has attracted a lot of interest over the years and as a result, many coverage protocols were proposed. In this survey, we first propose a taxonomy for classifying coverage protocols in WSNs. Then, we classify the coverage protocols into three categories (i.e. coverage aware deployment protocols, sleep scheduling protocols for flat networks, and cluster-based sleep scheduling protocols) based on the network stage where the coverage is optimized. For each category, relevant protocols are thoroughly reviewed and classified based on the adopted coverage techniques. Finally, we discuss open issues (and recommend future directions to resolve them) associated with the design of realistic coverage protocols. Issues such as realistic sensing models, realistic energy consumption models, realistic connectivity models and sensor localization are covered
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