Adverse Selection via Matching in Cooperative Fog Computing
Zexuan Yang, Li Wang, Yinan Ding, Mei Na Song · 2018
Due to the fast increasing of mobile data demands and limitation of edge devices in computing capability, it is significant to exploit fog computing to support future edge networks' demands. This paper has investigated a cooperative computing problem. By borrowing the concept of fog computing, fog nodes are allowed to collaborate and provide computing services to the requesters. Considering the hidden information of fog nodes as computing capability and channel status, the adverse selection model based on contract theory is formulated to stimulate the fog nodes to provide high quality of services and realize collaborative optimization of computing resources and communication resources, targeting on maximizing the utility of both the requesters and fog nodes. To solve the proposed multi-requesters and multi-cooperators contract design problem, variety matching algorithms can be exploited to optimize solutions with different objections. Simulation results have proved the effectiveness of the proposed scheme.