Energy-Efficient Coalition Formation in Sensor Networks: a Game-Theoretic Approach

TL;DR

This paper introduces a game-theoretic clustering algorithm for wireless sensor networks that improves energy efficiency and throughput by forming coalitions based on node energy levels.

Contribution

It proposes a novel coalitional game approach with Shapley value for energy-aware clustering in WSNs, addressing hotspot issues.

Findings

Enhanced energy efficiency in sensor networks

Increased network throughput

Effective mitigation of hotspot problem

Abstract

The most important challenge in Wireless Sensor Networks (WSNs) is the energy constraint. Numerous solutions have been proposed to alleviate the issue, including clustering. Game theory is an effective decision-making tool that has been shown to be effective in solving complex problems. In this paper, we employ cooperative games and propose a new clustering scheme called Coalitional Game-Theoretic Clustering (CGTC) algorithm for WSNs. The idea is to partition the entire network area into two regions, namely far and vicinity, in order to address the hotspot problem in WSNs, wherein nodes close to the base station (BS) tend to deplete their energy faster due to relaying the traffic load received from farther nodes. Then, coalitional games are utilized to group nodes as coalitions. The main factor in choosing coalition heads is the energy level of nodes so that the most powerful nodes play the role of heads. The Shapley value is adopted as the solution concept to our coalitional games. The results of simulations confirm the effectiveness of CGTC in terms of energy efficiency and improved throughput.