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• W3214343112 abstract "Mobile edge computing (MEC) is emerging as a promising paradigm to support the applications of Internet of Things (IoT). The edge servers bring computing resources to the edge of the network, so as to meet the delay requirements of the IoT devices’ service requests. At the same time, the edge servers can gain profit by leasing computing resources to IoT users and realize the allocation of computing resources. How to determine a reasonable resource leasing price for the edge servers and how to determine the number of resource purchased by users with different needs is a challenging problem. In order to solve the problem, this paper proposes a game-based scheme for resource purchasing and pricing aiming at maximizing user utility and server profit. The interaction between users and the edge servers is modeled based on Stackelberg game theory. The properties of incentive compatibility and envy freeness are theoretically proved, and the existence of Stackelberg equilibrium is also proved. A game-based user resource purchasing algorithm called GURP and a game-based server resource pricing algorithm called GSRP are proposed. It is theoretically proven that solutions of the proposed algorithms satisfy the individual rationality property. Finally, simulation experiments are carried out, and the experimental results show that the GURP algorithm and the GSRP algorithm can quickly converge to the optimal solutions. Comparison experiments with the benchmark algorithms are also carried out, and the experimental results show that the GURP algorithm and the GSRP algorithm can maximize user utility and server profit." @default.
• W3214343112 created "2021-11-22" @default.
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• W3214343112 date "2021-11-12" @default.
• W3214343112 modified "2023-10-16" @default.
• W3214343112 title "A Game-Based Scheme for Resource Purchasing and Pricing in MEC for Internet of Things" @default.
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• W3214343112 doi "https://doi.org/10.1155/2021/1951141" @default.
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