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.
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Acknowledgements
We thank the editor and anonymous reviewers for their valuable comments, which help us improve the quality of this paper.
Funding
This work is supported by National Natural Science Foundation of China (No. 62172124). It was also supported by the Shenzhen Basic Research Program (Project No. JCYJ20190806143011274).
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Li, Q., Wang, Z. & Du, H. Incentive mechanism design for value-decreasing tasks in dynamic competitive edge computing networks. J Comb Optim 49, 3 (2025). https://doi.org/10.1007/s10878-024-01228-5
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DOI: https://doi.org/10.1007/s10878-024-01228-5