Tracking of Moving Target in Wireless Sensor Network with Improved Network Life Time Using PSO

Abstract

Target tracking in wireless sensor networks (WSNs) is one of the highly researched applications. Work to be done in this area typically requires systematized groups of sensor nodes which monitors the target and delivers dimensions of a target’s position change or precise distance dimensions from the nodes to the target, and predicting those change in movement of the target too. These deliverables are sent to the centralized entity for the further processing. In the case of sensor faults and impulsive environments, these are, hard to achieve precisely in real practice. WSN having the constraints of limited sensing range, it is of immense significance to design mechanism which provides coordination amongst nodes for unfailing tracking and with a high probability too, at least the target can always be detected and tracked, while the entirety network energy expenditure can be reduced for longer network lifetime. Due to unpredicted nature of the target, design of target tracking mechanism demands prediction algorithm to be implemented for the prediction of target trajectory. Design also demands network to be optimized in terms of energy expenditure to cope with early draining of node’s battery which are very small in size and with low capacity, which in turns helps to increase the life time of the network. To overcome the said issues, proposed work uses target state dynamics to predict target trajectory and implementation of Particle Swarm Optimization for the network optimization to save on overall network energy expense and hence to increase network life time.