Joint Optimization of Energy and QoE with Fairness in Cooperative Fog Computing System

Abstract

Fog Computing as one of Mobile Edge Computing (MEC) paradigms deploys servers to the edge of networks to reduce the transmission latency. However, how to obtain the energy-effective cooperation policy among fog nodes to enhance the users' quality of experience (QoE) under fairness still remains a challenging issue, where the fairness ensures that fog nodes are encouraged to take part in cooperations. Therefore, we first build up a cooperative fog computing system to process offloading workload on the entire Fog layer by data forwarding. Then we propose a joint optimization problem of QoE (average response time) and energy (average energy consumption) in integrated fog computing process with fairness. After that, we prove the convexity of the optimization problem and design a Fairness Cooperation Algorithm to obtain the optimal fairness cooperation policy of all fog nodes. Finally, by comparing with baseline algorithm and Distributed Optimization Algorithm, the numerical results show that our algorithm can effectively reduce response time reduction and energy consumption.