Hybrid Grey Wolf Optimizer and Elitism Genetic Algorithm for Multi-objective IoT Service Placement in Fog Computing Environment
In response to the expanding use of the Internet of Things (IoT), fog computing was created to enhance cloud computing services and meet the requirement to process and store enormous volumes of newly created data. In this environment, we address the service placement problem by proposing a new hybrid meta-heuristic algorithm that combines the Grey Wolf Optimizer and the Elitism Genetic Algorithm. The iFogSim simulator is used to evaluate the performance of the proposed approach. The results were compared to metaheuristics from the literature: Elitism Genetic Algorithm and Grey Wolf Optimizer. Simulation results show that the proposed algorithm is more efficient than both the Grey Wolf Optimizer and the Elitism Genetic Algorithm in terms of execution time and total cost.
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