A Game-theoretic Framework for Revenue Sharing in Edge-Cloud Computing System

• Main Authors: Cao, Zhi, Zhang, Honggang, Liu, Benyuan, Sheng, Bo
• Format: Conference Proceeding
• Language: English
• Subjects: Cloud computing; Edge computing; Games; Nash equilibrium; Servers; Task analysis
• ISSN: 2374-9628
• DOI: 10.1109/PCCC.2018.8710866

We introduce a game-theoretic framework to explore revenue sharing in an Edge-Cloud computing system, in which computing service providers at the edge of the Internet (edge providers) and computing service providers at the cloud (cloud providers) collectively provide computing resources to clients (e.g., end users or applications) at the edge. Different from traditional cloud computing, the providers in an Edge-Cloud system are independent and self-interested. To achieve high system-level efficiency, the manager of the system adopts a task distribution mechanism to maximize the total revenue received from clients and also adopts a revenue sharing mechanism to split the received revenue among computing servers (and hence service providers). Under those system-level mechanisms, service providers attempt to game with the system in order to maximize their own utilities, by strategically allocating their resources (e.g., computing servers). Our framework models the competition among the providers in an Edge-Cloud system as a non-cooperative game. We have shown the existence of Nash equilibrium in the game both theoretically and practically through simulations and experiments on an emulation system that we have developed. We find that revenue sharing mechanisms have a significant impact on the system-level efficiency at Nash equilibria, and surprisingly the revenue sharing mechanism based directly on actual contributions can result in significantly worse system performance than Shapley value sharing mechanism and Ortmann proportional sharing mechanism. Our framework provides an effective economics approach to the understanding and designing of efficient Edge-Cloud computing systems.