Optimization of Routing and Cluster Head Selection in WSN: A Survey

In wireless sensor networks, optimizing the network lifespan is a major issue. There is a requirement to learn and make effective, powerful communication protocols to play with the challenges of wireless sensor networks (WSNs) to create a long-lasting, functional network. Traditional approaches that use fixed equations to solve these issues call for very intricate computations. Artificial intelligence (AI) algorithms, such as machine learning and deep learning techniques, which offer high accuracy, reduced costs, and extended network lifetimes, have given rise to new approaches to resolving these issues. In this paper, we present an overview of several research on machine learning strategies that have been used to address a variety of problems in WSNs, particularly in the fields of routing and head selection for each network cluster.