An Efficient Cluster Head Selection Approach for Collaborative Data Processing in Wireless Sensor Networks

Abstract

Since wireless sensor networks (WSNs) consist of nodes with limited battery power, collaborative data processing and balanced energy consumption should be considered as the key issue. This paper proposes an efficient cluster head selection approach for collaborative data processing in WSNs. The proposed algorithm designs an effective energy-efficient model to select the optimal cluster heads among all nodes fairly, which helps to reduce the impact of the monitoring scheme on the lifetime of network. Experimental results show that the proposed protocol is able to reduce energy consumption and obtain higher efficiency as well as effectively prolonging the lifetime of network more than a few existing cluster-based routing protocols.