Title: Maximum-lifetime data aggregation for wireless sensor networks with cooperative communication
Authors: Hongli Xu; Liusheng Huang; Haipei Sun
Addresses: School of Computer Science and Technology, University of Science and Technology of China, Hefei, Anhui 230027, China; Suzhou Institute for Advanced Study, University of Science and Technology of China, Suzhou, Jiangsu 215123, China ' School of Computer Science and Technology, University of Science and Technology of China, Hefei, Anhui 230027, China; Suzhou Institute for Advanced Study, University of Science and Technology of China, Suzhou, Jiangsu 215123, China ' School of Computer Science and Technology, University of Science and Technology of China, Hefei, Anhui 230027, China
Abstract: Cooperative communication becomes an attractive technology to avoid the signal fading for wireless transmissions. Multiple nodes can cooperatively transmit the data packets to a receiver so as to improve the spatial diversity and save the power consumption. As data aggregation is one of the most important operations for surveillance applications, this paper studies the maximum-lifetime data aggregation with cooperative communication (MLDAC) in wireless sensor networks. We first analyse the optimal power allocation for cooperative data aggregation, and propose the LPS algorithm which maximises the network lifetime through iteratively adjusting the selection of the cooperative node pairs. We also present a distributed algorithm (called DLPS), in which each node decides to participate into the cooperative transmission only with local information. The simulation results show that the LPS and DLPS algorithms will help to prolong the network lifetime by 17.9% and 12.7% compared with the traditional algorithm.
Keywords: data aggregation; cooperative communication; network lifetime; wireless sensor networks; WSNs; signal fading; spatial diversity; energy consumption; simulation.
DOI: 10.1504/IJSNET.2016.075369
International Journal of Sensor Networks, 2016 Vol.20 No.3, pp.187 - 198
Accepted: 21 Jun 2015
Published online: 17 Mar 2016 *