E-MOGWO Algorithm for Computation Offloading in Fog Computing

Despite the advances mobile devices have endured, they still remain resource-restricted computing devices, so there is a need for technology that supports these devices. An emerging such resource-constrained called fog computing. End can offload task to close-by nodes improve quality of service and experience. Since computation offloading multiobjective problem, we consider many factors before taking decisions, as length, remaining battery power, latency, communication cost, etc. This study uses grey wolf optimization (MOGWO) technique optimizing decisions. first time MOGWO has been applied in A gravity reference point method also integrated with propose an enhanced (E-MOGWO) algorithm. It finds optimal target by into account two parameters, i.e., energy consumption computational heterogeneous, scalable, multi-fog, multi-user environment. The proposed E-MOGWO compared MOGWO, non-dominated sorting genetic algorithm (NSGA-II) accelerated particle swarm (APSO). results showed achieved better than existing approaches regarding consumption, number tasks successfully executed.