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Optimal Service Selection and Placement Based on Popularity and Server Load in Multi-access Edge Computing

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Abstract

The appearance of mobile edge computing (MEC) addresses the problems of low bandwidth and high latency in the network. However, the services deployed by MEC servers are limited and have limited coverage. When mobile devices move away from the MEC servers deployed by application services as users move, it will lead to MEC service timeout or even service interruption. The dynamic deployment of edge services can change the deployment location of services to meet the service demand of mobile terminals, thus providing users with better service quality. The service deployment problem is a very considerable research contents within edge computing. In this paper, we introduce a load and service popularity based service deployment strategy for the service deployment problem. This strategy takes minimizing the response delay of service request as the optimization goal, considers the main factors such as service popularity and server load, establishes a service deployment model, and then solves the optimal service deployment method through an improved ant colony algorithm. The results of the experiments indicate that the proposed MEC service deployment strategy can improve the request response rate and shorten the waiting time of users.

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Acknowledgements

The work was supported by Open project of MNR Key Laboratory of Plateau Geohazards Monitoring & Warning and Ecological Conservation & Restoration, Open project of Key Laboratory of Southeast Coast Marine Information Intelligent Perception and Application, Ministry of Natural Resources (KFJJ20220203), Henan Key Laboratory of Intelligent Manufacturing Equipment Integration for Superhard Materials (JDKJ2022-05), Open project of Jiangsu Wind Power Engineering Technology Center (ZK22-03-03).

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Authors and Affiliations

  1. MNR Key Laboratory of Plateau Geohazards Monitoring & Warning and Ecological Conservation & Restoration, Kunming, People’s Republic of China

    Chunlin Li & Cheng Huang

  2. Key Laboratory of Southeast Coast Marine Information Intelligent Perception and Application, Ministry of Natural Resources, Zhangzhou, 363000, People’s Republic of China

    Chunlin Li

  3. Department of Computer Science, Wuhan University of Technology, Wuhan, 430063, People’s Republic of China

    Chunlin Li, Qingzhe Zhang & Youlong Luo

  4. Henan Key Laboratory of Intelligent Manufacturing Equipment Integration for Superhard Materials, Xin Zheng, 451191, People’s Republic of China

    Chunlin Li

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  1. Chunlin Li
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  2. Qingzhe Zhang
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Correspondence to Chunlin Li or Cheng Huang.

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Li, C., Zhang, Q., Huang, C. et al. Optimal Service Selection and Placement Based on Popularity and Server Load in Multi-access Edge Computing. J Netw Syst Manage 31, 15 (2023). https://doi.org/10.1007/s10922-022-09703-2

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  • DOI: https://doi.org/10.1007/s10922-022-09703-2

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