Framework for Optimizing Energy Conversation Based on Metaheuristic Algorithms

Abstract

Wireless sensor networks collect information from the environment and send it to the base station. Data transmission and aggregation consume more electricity because of the nodes stuck in a loop. We employ a metaheuristic approach to optimizing the node so as to minimize energy consumption. We formulate a framework that will improve energy efficiency by employing various metaheuristic algorithms like ant colony algorithm, dragonfly algorithm, genetic algorithm, bat algorithm, Particle swarm optimization, Artificial Bee Colony, Grey Wolf Optimizer, Lion Optimization Algorithm, Mayfly Optimization Algorithm, Owl Search Algorithm, Artificial Fish Swarm Algorithm, Dolphin Echolocation, Cuckoo Search, and firefly algorithm, among others. In this article, there are comprehensive descriptions of basic concepts such as security and interoperability (interoperability), standards and scalability (standards), complexity and data management (complexity), and Quality of Service (QoS). Additionally, this paper discusses current technologies when deploying them. This study aims to investigate possibilities for research along the lines of Artificial Intelligence (AI) within the domain of wireless sensor networks (WSNs), both from theoretical and practical points of view.