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.