Single-service Workflow Computational Offloading with Constrained Subtasks in The Multi-Edge Server Scenario

Energy consumption is one of the main costs of running MEC (Multi-access Edge Computing) systems, and single-service workflows are composed of multiple constrained subtasks that incur a significant portion of energy consumption when offloading these subtasks to different edge nodes to complete computation. We propose an improved genetic algorithm GTGA (Game Theory Genetic Algorithm) to find an offloading scheme to minimize the energy consumption of single-service workflow computational offloading, so that each workflow in the terminal generated service workflow can achieve the goal of minimum energy consumption when calculating offloading.