基于遗传算法的移动边缘计算环境下服务工作流的计算卸载

Computational unloading of service workflow in mobile edge computing environment based on genetic algorithm

计算卸载需要考虑到不同的服务器终端与移动设备的网络连接性能、卸载任务的能耗等,为了实现最优卸载,基于遗传算法进行工作流计算卸载优化,制定移动服务工作流制定计算卸载计划,设定5个工作流调度任务,通过编码、适应度函数、选择算子、交叉算子、变异算子确定是否在本地卸载,最后通过仿真实验对该算法进行验证,结果表明:GA算法提高了卸载的成功率,降低了终端能耗。移动边缘计算环境服务下的计算卸载可以通过GA算法优化完成。

In order to achieve optimal unloading,workflow calculation and unloading optimization is carried out based on genetic algorithm.Mobile service workflow is formulated to make calculation and unloading plan,and five workflow scheduling tasks are set up,and it is determined whether to unload locally by encoding,fitness function,selection operator,crossover operator and mutation operator.Finally,the algorithm is verified by simulation experiments.The results show that GA algorithm improves the success rate of unloading and reduces the terminal energy consumption.The computational uninstallation in mobile edge computing environment can be optimized by GA algorithm.