Partial Offloading with Stable Equilibrium in Fog-cloud Environments using Replicator Dynamics of Evolutionary Game Theory

In this research, we propose a solution for partial offloading based on the replicator equation of evolutionary game theory. The ultimate goal is for users to be in a stable equilibrium based on their priorities in terms of energy consumption, latency, and computational cost so that no user is willing to change his/her strategy. The results of solving the replicator equation followed by statistical analysis show that the proposed method has a remarkable performance improvement compared to the state-of-the-art methods. Our method not only shows a better average based on the weighted combination of energy consumption, latency, and cost but also has a lower variance compared to the full local execution and the full offloading methods. Our results also show that when the number of users is very large, the system can reach equilibrium with the least amount of information exchange among players.

在本项研究中，我们基于进化博弈论中的复制者方程，提出了一种部分卸载的解决方案。其最终目标是使用户根据其在能耗、延迟和计算成本方面的优先级，达到一个稳定的均衡状态，从而使得没有任何用户愿意改变其策略。通过求解复制者方程并进行统计分析所得到的结果表明，与现有技术相比，所提出的方法具有显著的性能提升。我们的方法不仅在能耗、延迟和成本加权组合的平均值上表现出更优，而且与全本地执行和全卸载方法相比，具有更低的方差。此外，我们的研究结果还表明，当用户数量非常庞大时，系统可以在玩家之间进行最少的信息交换的情况下达到均衡状态。