Static cluster and dynamic cluster head (SCDCH) adaptive prediction-based algorithm for target tracking in wireless sensor networks

摘要

Wireless sensor networks consist of large number of sensor nodes that have an ability to interact with the surrounding environment. The importance of finding the suitable protocol to estimate the trajectory for any moving target in a certain environment is a case of study for researchers. In this paper, new and accurate protocol for target tracking with minimum energy consumption is proposed. The proposed approach uses the static cluster and dynamic cluster head mechanism (SCDCH) to collect data from the active nodes, and then forwards it to the cluster head (CH), which in turn will send the collected data to the base station, without changing cluster border during the network's lifetime. Simulation results show that the proposed protocol has higher accuracy and save more energy compared with static clustering protocols which in turn increases the network lifetime.