Energy balancing through cluster head selection using K-Theorem in homogeneous wireless sensor networks

TL;DR

This paper introduces a novel energy-efficient cluster head selection method using K-theorem in homogeneous wireless sensor networks, enhancing network lifetime and scalability by balancing energy consumption and reducing long-range communication.

Contribution

It proposes a modified WSN architecture with a resource-rich coordinator node and a K-theorem-based cluster head selection algorithm, improving energy efficiency and robustness.

Findings

Increased network lifetime through energy balancing.

Enhanced scalability and robustness against node mobility.

Reduced energy consumption by minimizing long-range communication.

Abstract

The objective of this paper is to increase life time of homogeneous wireless sensor networks (WSNs) through minimizing long range communication and energy balancing. Sensor nodes are resource constrained particularly with limited energy that is difficult or impossible to replenish. LEACH (Low Energy Adaptive Clustering Hierarchy) is most well-known cluster based architecture for WSN that aims to evenly dissipate energy among all sensor nodes. In cluster based architecture, the role of cluster head is very crucial for the successful operation of WSN because once the cluster head becomes non functional, the whole cluster becomes dysfunctional. We have proposed a modified cluster based WSN architecture by introducing a coordinator node (CN) that is rich in terms of resources. This CN take up the responsibility of transmitting data to the base station over longer distances from cluster heads. We have proposed a cluster head selection algorithm based on K-theorem and other parameters i.e. residual energy, distance to coordinator node, reliability and degree of mobility. The K-theorem is used to select candidate cluster heads based on bunch of sensor nodes in a cluster. We believe that the proposed architecture and algorithm achieves higher energy efficiency through minimizing communication and energy balancing. The proposed architecture is more scalable and proposed algorithm is robust against even/uneven node deployment and node mobility.