A Game-Based Scheme for Resource Purchasing and Pricing in MEC for Internet of Things

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 server...

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Autores principales:	Yajing Leng, Ming Wang, Bowen Ma, Ying Chen, Jiwei Huang
Formato:	article
Lenguaje:	EN
Publicado:	Hindawi-Wiley 2021
Materias:	Technology (General) T1-995 Science (General) Q1-390
Acceso en línea:	https://doaj.org/article/bd3d9b4bb9634d9ca5db352d2aba11cb
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id	oai:doaj.org-article:bd3d9b4bb9634d9ca5db352d2aba11cb
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spelling	oai:doaj.org-article:bd3d9b4bb9634d9ca5db352d2aba11cb2021-11-22T01:10:22ZA Game-Based Scheme for Resource Purchasing and Pricing in MEC for Internet of Things1939-012210.1155/2021/1951141https://doaj.org/article/bd3d9b4bb9634d9ca5db352d2aba11cb2021-01-01T00:00:00Zhttp://dx.doi.org/10.1155/2021/1951141https://doaj.org/toc/1939-0122Mobile 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.Yajing LengMing WangBowen MaYing ChenJiwei HuangHindawi-WileyarticleTechnology (General)T1-995Science (General)Q1-390ENSecurity and Communication Networks, Vol 2021 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Technology (General) T1-995 Science (General) Q1-390
spellingShingle	Technology (General) T1-995 Science (General) Q1-390 Yajing Leng Ming Wang Bowen Ma Ying Chen Jiwei Huang A Game-Based Scheme for Resource Purchasing and Pricing in MEC for Internet of Things
description	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.
format	article
author	Yajing Leng Ming Wang Bowen Ma Ying Chen Jiwei Huang
author_facet	Yajing Leng Ming Wang Bowen Ma Ying Chen Jiwei Huang
author_sort	Yajing Leng
title	A Game-Based Scheme for Resource Purchasing and Pricing in MEC for Internet of Things
title_short	A Game-Based Scheme for Resource Purchasing and Pricing in MEC for Internet of Things
title_full	A Game-Based Scheme for Resource Purchasing and Pricing in MEC for Internet of Things
title_fullStr	A Game-Based Scheme for Resource Purchasing and Pricing in MEC for Internet of Things
title_full_unstemmed	A Game-Based Scheme for Resource Purchasing and Pricing in MEC for Internet of Things
title_sort	game-based scheme for resource purchasing and pricing in mec for internet of things
publisher	Hindawi-Wiley
publishDate	2021
url	https://doaj.org/article/bd3d9b4bb9634d9ca5db352d2aba11cb
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A Game-Based Scheme for Resource Purchasing and Pricing in MEC for Internet of Things

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