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An Effective Resource Allocation Approach Based on Game Theory in Mobile Edge Computing

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Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1156))

Abstract

As a promising technology, mobile edge computing (MEC) can provide an IT service environment and cloud-computing capabilities at the edge of the mobile network, and also can reduce latency, improve user experience. In this paper, we have proposed a MEC system consisting of one privately service provider (SP) and multiple mobile users (MU). A game theory approach for resource allocation optimization is proposed to analyze the interaction between the leader SP and the followers MUs. We have introduced the congestion factor between different MUs. In addition, we prove the existence of the Nash equilibrium (NE) by game theory method and design an efficient the best response (BR) algorithm to solve this problem. An optimal equilibrium strategy can be obtained by the BR algorithm, and experiment results have demonstrated the efficiency and feasibility of the algorithm.

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Acknowledgments

This work is partly supported by the National Natural Science Foundation of China (Nos. 61872044, 61902029), the Key Research and Cultivation Projects at Beijing Information Science and Technology University (No. 5211910958), the Supplementary and Supportive Project for Teachers at Beijing Information Science and Technology University (No. 5111911128), Beijing Municipal Program for Top Talent Cultivation (CIT & TCD201804055) and Qinxin Talent Program of Beijing Information Science and Technology University.

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Correspondence to Bilian Wu .

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Wu, B., Chen, X., Chen, Y., Li, Z. (2020). An Effective Resource Allocation Approach Based on Game Theory in Mobile Edge Computing. In: Zheng, Z., Dai, HN., Tang, M., Chen, X. (eds) Blockchain and Trustworthy Systems. BlockSys 2019. Communications in Computer and Information Science, vol 1156. Springer, Singapore. https://doi.org/10.1007/978-981-15-2777-7_31

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  • DOI: https://doi.org/10.1007/978-981-15-2777-7_31

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-15-2776-0

  • Online ISBN: 978-981-15-2777-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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