Incentive mechanism design for value-decreasing tasks in dynamic competitive edge computing networks

Abstract

With the rapid development of network architectures and application technologies, there is an increasing number of latency-sensitive tasks generated by user devices, necessitating real-time processing on edge servers. During peak periods, user devices compete for limited edge resources to execute their tasks, while different edge servers also compete for transaction opportunities. This article focus on resource allocation problems in competitive edge networks with multiple participants. Considering the decreasing value of tasks over time, a Greedy Method with Priority Order (GMPO) mechanism based on auction theory is designed to maximize the overall utility of the entire network. This mechanism consists of a short-slot optimal resource allocation phase, a winner determination phase that ensures monotonicity, and a pricing phase based on critical prices. Theoretical analysis demonstrates that the GMPO mechanism can prevent user devices from engaging in dishonest transactions. Experimental results indicate that it significantly enhances the overall utility of competitive edge networks.