Uneven clustering in wireless sensor networks: A comprehensive review

Abstract

The key component of Wireless Sensor Networks (WSNs) is the sensor node, which has a battery with limited energy, therefore the power utilization of the batteries must be optimized. Optimization in WSNs is required for energy efficiency and life span improvement. Several optimization techniques are proposed by researchers and clustering is one of the prominent techniques, in the power management of wireless sensor networks. Clustered WSNs provide advantages over normal WSNs such as improved bandwidth utilization, less overhead, enhancement in connectivity of links, efficiently balanced sensor nodes, stability in network topology, lesser delay, and reduced routing tables. There are two ways of clustering: even clustering and uneven clustering. In even clustering, the hotspot problem is caused by the inequality of the power consumed by the WSN's member nodes, which reduces the lifetime of the WSNs. To address the issue of hot spots, uneven clustering types are employed to balance the load among the cluster heads (CHs). Uneven cluster sizes have a significant impact on the communication range and reliability of the networks. Diversified clustering properties and methods of uneven clustering are rigorously reviewed. Uneven clustering characteristics and algorithms are classified and explained in the paper. In this paper, the authors reviewed all the algorithms for making clusters to balance uneven energy consumption and increase the lifespan of WSNs.