An energy aware cluster inspired routing protocol using multi strategy improved crayfish optimization algorithm for guaranteeing green communication in IoT - Chithra, R.; Sarumathiy, C. K.; Padma, E.; Arulkumar, R. (Scientific reports, 2025)
Internet of things (IoT) has a significant impact on environmental and economic factors for interconnecting billions or trillions of devices that utilize various types of sensors during communications using Internet. Energy is identified as the heart of smart IoT applications since it permits the sensors to carry out their operations. Even though, sensors necessitate a small amount of energy for operations, rapid energy drain when billions and trillions of them interconnect is determined to crumble their performance by influencing energy stability. Clustering is the potential energy managing green communication mechanism which when implemented using metaheuristic techniques helps in achieving required quality of service by facilitating near-optimal solutions. In this paper, mult strategy-improved crayfish optimization algorithm-based intelligent clustering mechanism (MSCFOAICM) is proposed as a solution to the NP-hard problem of achieving green communication in IoT with maximized network lifetime. This MSCFOAICM scheme used a multi-objective fitness function that considered factors of delay, energy, distance, jitter and packet forwarding potential into account such that energy potent nodes are selected as cluster heads (CHs) during the clustering process. It uses multi-strategy-improved crayfish optimization algorithm for CH selection for establishing a better trade-off between exploration and exploitation. It then used a hybrid BWM-TOPSIS multicriteria decision making model for determining nodes’ trust using direct and indirect interaction to prevent selection of malicious nodes as CHs. This protocol also prevented low energy nodes to be selected as CHs depending on residual energy estimation during the trust computation process. The number of clusters built during the implementation is determined to be optimal as it aids in sustaining maximized energy and extending network lifetime. The results of MSCFOAICM scheme confirm better throughput of 18.14%, operating IoT nodes of 19.42% and reduced mean transmission delay of 18.42%, compared to the baseline schemes.