Green communication in sensor enabled IoT: integrated physics inspired meta-heuristic optimization based approach

Green communication plays a significant role in sensor enabled IoT. Energy is at the focal point in the smart application of the IoT which enables the sensors to be work. The faster energy depletion causes the hindrance in efficient functioning of the sensors. An energy-efficient scheme is required to prevent the faster reduction of energy from sensors in IoT. Metaheuristic techniques are most effective to solve such problems with the near-optimal solution as heuristic techniques are not suitable for such problem, they may turn into NP-hard problem in dense area sensor networks. Most of the optimization-based energy-efficient techniques suffer from unstable energy depletion problem because nodes near to the base station (BS) have more traffic load. In this paper, an energy balanced integrated atom swarm and electromagnetic force optimization (iASEF) scheme is proposed to overcome the energy depletion problem. The iASEF consists of (a) A linear programing problem of clustering that consisting of an objective function and constraints based on node degree, intra-cluster distance, residual energy of node and inter-cluster distance, (b) optimal routing problem. Atom search optimization has been employed to solve linear problem to find optimal cluster head (CH) among sensors. Electromagnetic force optimization has been used to solve routing problem to find next hop for data forwarding between the CH and BS. The simulation results demonstrate that the proposed iASEF scheme achieves substantial enhancement over the state-of-art algorithms.