Abstract How to use the resources of the edge cloud more reasonably, reduce the energy consumption of machine equipment and ensure the shortest time for task completion are the challenges faced in cloud robot computation offloading research. In this paper, multiple heterogeneous cloud robot computing offloading problems are converted into game-type problems, and the computation-intensive tasks are divided to achieve partial offloading of tasks. An improved distributed game theory algorithm is designed to make each cloud robot's computation offloading strategy reaches the Nash equilibrium state, which maximizes the benefits of multiple participants, reduces the network load pressure of the central cloud, and reduces the transmission delay of computation offload. Simulation results show that the improved distributed game computation offload algorithm proposed enables cloud robots to reduce local computing energy consumption and shorten the average task completion time, greatly improving the edge cloud service quality.

中文翻译：

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基于改进博弈论的云机器人计算卸载算法

摘要 如何更合理地利用边缘云资源，降低机器设备能耗，保证任务完成时间最短，是云机器人计算卸载研究面临的挑战。本文将多个异构云机器人计算卸载问题转化为博弈类问题，对计算密集型任务进行划分，实现任务的部分卸载。设计了一种改进的分布式博弈论算法，使每个云机器人的计算卸载策略达到纳什均衡状态，最大限度地发挥了多个参与者的利益，降低了中心云的网络负载压力，减少了计算卸载的传输延迟。