Abstract

In mobile ad hoc networks (MANETs), the efficient energy-efficient cluster head selection (EECHS) is a significant issue. When an appropriate cluster head (CH) is chosen, MANETs'''' energy efficiency improves. Clusters are built in MANETs to facilitate communication between nodes. The EECHS problem has been addressed using a variety of clustering strategies, including distributed clustering and cluster-based routing. However, these approaches require high overhead and complexity, leading to suboptimal performance. Therefore, it is necessary to develop an algorithm that can select the best CH to facilitate efficient energy-efficient communication in MANETs. In this regard, the Firefly Algorithm (FA) has been proposed as an effective approach to solving the EECHS problem. FA is a type of swarm intelligence-based meta-heuristics algorithm inspired by the behavior of fireflies. FA is a simple and efficient optimization method that can be used to select the best CH in MANETs. The method has a number of benefits, including enhanced convergence rate and local search functionality. FA is also computationally effective and can adapt to shifting network conditions. This essay offers a thorough evaluation of the literature on the use of FA in MANETs to address the EECHS. Along with comparisons of their performances, a thorough examination of the suggested methodologies and algorithms is offered. Last but not least, various difficulties and potential research paths pertaining to the usage of the FA are explored.