Adaptive Node Degree Adjustment Based Power Control Method for Wireless Sensor Networks

Abstract

Properly adjusting the transmission power of the wireless sensor nodes has shown to be an effective approach to reduce energy consumption and to improve the network reliability. I In this paper, an adaptive Node Degree adjustment based Power Control method for wireless sensor networks (NDPC) is proposed to dynamically adjust the transmission power of the nodes. In NDPC, each node is embedded with a fuzzy neural controller which is used to adjust the target node degree so as to control the communication range properly. The fuzzy neural controller consists of two Fuzzy Inference Systems (FIS). One adopts closed-loop feedback mechanism to adjust the target node degree according to the residual energy. The other adjusts the communication range by a self-learning neural network to control the transmission power based on the target node degree. Consequently, the actual energy consumption of the node is reduced while keeping the desired node degree. Several simulation experiments are conducted to evaluate the performance of NDPC, and the results show that NDPC can reduce the actual energy consumption as well as extend the network lifetime.