Performance optimization and simulation based on target tracking in wireless sensor networks

Sensors should be selected elaborately to fulfil the sensing task in wireless sensor networks, sensor selection is based on the tradeoff between information utility achieved by the sensor measure and energy overhead to fetch the measure. But the users' requirements for quality of service (QoS) aren't yet involved in the process of sensor collaboration. A novel algorithm named A-DCS (Adaptively Dynamic Collaborative Self-organization) is proposed based on target tracking in this paper. Detection and estimation can be solved at the same tine in this algorithm. Given the threshold of detection probability the set of candidate sensor nodes can be confirmed, the sensor node with the maximum detection probability is selected to be the cluster head. Then the sequence of cluster members participating in the sensing task can be made adaptively according to the given threshold of estimation variable, so the total number of cluster member should be ascertained in our method, and the corresponding energy consumption is given out. Basing on the energy consumption under the condition of different detection probability and estimation accuracy the appropriate detection probability and estimation accuracy should be chosen to prolong the lifetime of networks. Simulation results demonstrate that this algorithm is superior to IDSQ and DCS in terms of the tracking accuracy and the energy consumption. This method can also be used in the problem of estimation in wireless sensor network.