Energy-Aware Distributed Intelligent Data Gathering Algorithm in Wireless Sensor Networks

Abstract

To plan the data collecting path for the mobile collector in wireless sensor network (WSN), an efficient energy-aware distributed intelligent data gathering algorithm (DIDGA) is proposed, which includes cluster formation and path formation phases. In cluster formation phase, an energy-efficient distributed clustering scheme is proposed to form a coverage-efficient WSN, which constructs a minimum connected dominating set (MCDS) based on maximal independent sets (MISs) in distributed and localized manner, and the node with more power is selected to be the cluster head in turn to prolong the network lifetime. In path formation phase, a path formation optimized algorithm (PFOA) is proposed to resolve the path formation NP problem with dynamic requirements. Then DIDGA uses the cluster head relay mechanism for planning the data gathering path. Compared with existed algorithms, detailed simulation results show that the proposed DIDGA can reduce average hop counts, average data gathering time, energy consumption, increase the efficiency of event detection ratio and prolong the network lifetime.