Energy-predicted shortest routing tree algorithm in wireless sensor networks

Abstract

Wireless sensor networks (WSNs) consists of unattended sensors with limited storage, energy (battery power) and computational and communication capabilities. Since battery power is the most crucial resource for sensor nodes, the energy prediction and the shortest path is special important. In this paper, we present an energy-predicted shortest routing tree algorithm (EP-SRT) for wireless sensor networks. it improves energy utility by changing the activity of wireless communication module of sensor nodes, energy prediction model and state transition of sensor nodes, while employs clustering and the principle of Prim and Djkstra to build the shortest routing tree to prolong network lifetime. Simulation results show that EP-SRT performs better than MIP and SRT algorithm with high-density deployment and high traffic. © 2008 Springer Berlin Heidelberg.