Joint optimization of number and allocation of clusters for wireless sensor networks

Abstract

Wireless sensor networks are an important new technology for remote monitoring. How to organize the nodes in a network remains a core practical problem. Node clustering is the most popular technique to increase the energy efficiency of a wireless sensor network, but the number of clusters greatly influences two performance metrics — data reliability and energy efficiency. Present methods treat these two metrics separately. To address this gap, we here introduce a joint optimal clustering technique (JOC), which optimizes both the number of clusters and the clustering process by considering intra and inter-cluster communication cost, link quality and traffic congestion so that both reliability and energy efficiency are maximized. We used simulation to compare JOC with HEED, the most popular of current clustering techniques. The results show that JOC improves network lifetime and reliability significantly.