Designing green IoT communication by adaptive spotted hyena tunicate swarm optimization‐based cluster head selection

Abstract

AbstractThe Internet of Things (IoT) has completely transformed the digital as well as virtual worlds of interconnected objects. In today's environment, the IoT describes a critical enabler for a broader variety of applications. Energy is at the center of the smart IoT application that allows the sensors to function. The sensors' ability to perform efficiently is hampered by rapid energy loss. To avoid the rapid loss of energy from sensors in the IoT, and energy‐effective method is necessary. Because heuristic approaches are not ideal for these issues and may turn into NP‐hard problems, meta‐heuristic techniques are mainly successful in solving various problems with near‐optimal solutions. This paper intends to develop a novel clustering protocol in Green IoT using a well‐performing novel hybrid adaptive meta‐heuristic algorithm. Here, an energy‐efficient clustering is performed by the hybrid spotted hyena optimization (SHO) and tunicate swarm algorithm (TSA) referred to as adaptive spotted hyena tunicate swarm optimization (ASHTSO) by deriving a multi‐objective function with “distance, energy, delay, security, and QoS”. The simulation findings show that the suggested technique outperforms existing algorithms significantly.