Partitioning Sensors by Node Coverage Grouping in Wireless Sensor Networks

The study of wireless Sensor Networks (WSN)recently has drawn a lot of attention. Such networks are composed of a large number of tiny wireless sensors, which have limited calculating capability as well as limited power typically supplied by microelectronics hardware. How to prolong network lifetime while maintaining a sufficient sensing area has been one of the most important issues in WSN research. In a high-density environment of sensor networks, excessive working sensors could cause several problems, such as excessive sensing or channel congestion. In this paper, we present a novel approach to partition sensors in the WSN, called node coverage grouping (NCG). Sensors in the connectivity group are within sensing range of each other, and data collected by sensors in a connectivity group are assumed to be similar. In this paper, we also prove that partitioning n nodes by node coverage grouping into connectivity groups is a NP-hard problem. Then we propose a heuristic algorithm of node coverage grouping with the time complexity of O(n³). The experimental results show that the NCG outperforms the LDAS and the PEAS methods in terms of the number of living nodes, the number of working nodes, and the coverage with the proceeding of system lifetime.