Wireless Sensor Networks ( Wsns )

3385 WordsOct 17, 201414 Pages
Energy consumption and coverage are common design issues in Wireless Sensor Networks (WSNs). For that reason, it is vital to consider network coverage and energy consumption in the design of WSN layouts. Because selecting the optimal geographical positions of the nodes is usually a very complicated task, we propose a novel heuristic search technique to solve this problem. Our approach is a multi-population search algorithm based on the Particle Swarm Optimization (PSO). The goal of this algorithm is to search for sensor network layouts that maximize both the coverage and lifetime of the network. Unlike traditional PSO, our algorithm assignes a swarm to each sensor in the network and a global network topology is used to evaluate the…show more content…
The Design of sensor layouts that account for both network coverage and power consumption is a difficult problem. Because WSN may have large number of nodes, the task of selecting the optimal geographical positions of the nodes can be very complicated. Therefore, we propose a cooperative particle swarm algorithm as a heuristic to address the problem of wireless sensor layout design. In our approach we assign a swarm to each node in the network. Each swarm will search for optimal $x$ and $y$ positions for its associated sensor. A global network layout, consisiting of the coordinates found by the best particles, will be maintained by the algorithm. The lifetime and coverage of this global layout will be used to measure the quality of each particle 's position. We hypothesize that by splitting the swarms across the set of sensors, our alorithm with obtain a finer-grained credit assignment, and reduce the chance of neglecting a good solution for a specific portion of the solution vector. We will verify this hypothesis by comparing our algorithm to several tradtional single-population search techniques. section{Background} subsection{Layout Optimization} Layout optimization for wireless sensor networks consists of finding the coordinates for a set of sensors that maximizes the lifetime and coverage for the sensor network. Placement of the sensors is bounded within a two-dimensional square region with an upper left

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