Energy-Efficient Fair Cooperation Fog Computing in Mobile Edge Networks for Smart City

Smart city as a new paradigm for future city development leads to a large amount of computing workload and high network latency especially with artificial intelligence algorithms. Fog computing, as one of the mobile edge computing paradigms, deploys some servers at the edge of mobile networks to solve these problems. However, it still remains a challenging issue how to obtain the energy-effective cooperation policy among fog nodes (FNs) to enhance the users' quality of experience (QoE) under fairness, where the fairness ensures that FNs are willing 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 formulate a joint optimization problem of QoE and energy in integrated fog computing process with fairness. After that, we prove the convexity of the optimization problem and design a fairness cooperation algorithm (FCA) to obtain the optimal fairness cooperation policy of all FNs. Finally, numerical results show that our FCA can quickly converge to its solution compared with three traditional convex optimization approaches, and FCA can effectively reduce the time overhead and the energy consumption compared to baseline algorithm and distributed optimization algorithm.