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Resource management and switch migration in SDN-based multi-access edge computing environments

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Abstract

As the growing of data volumes due to the successive development of new mobile devices and the creation of new applications, the emergence of multi-access edge computing can successfully improve quality of service based on reduced latency and lower system energy consumption. The introduction of software-defined networking technologies in multi-access edge computing environments supports access to more network devices and enhances the scalability and service management flexibility of mobile edge computing environments. The limited nature of computing resources in mobile edge computing environments makes resource management a critical issue. Therefore, to minimize the energy consumption and latency of task execution in mobile edge computing environment, and to ensure reasonable resource allocation during task execution, a resource management strategy based on multi-objective optimization in edge computing environment is proposed. In this strategy, the overall energy consumption weighting and minimization problem is solved by optimizing the management of communication and computing resources, and an improved NSGA-II algorithm is proposed to rationally allocate communication and computational resources for each task. To deal with load imbalance caused by large traffic fluctuations in multi-access edge computing environments based on software-defined networks, in this paper, a load-balancing-oriented switch migration strategy is proposed in which a switch migration algorithm based on an improved ant colony algorithm is proposed to optimally select the switch migration process so that the static deployment of the controller adapts to the changing needs of dynamic flows in the network. Experimental results demonstrate that the proposed resource management strategy minimizes the latency and energy consumption during task execution and increases resource utilization and average throughput of servers. The proposed switch migration strategy can effectively achieve load balancing and reduce the response time.

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Acknowledgements

The work was supported by open project of State Key Laboratory of Safety and Health for Metal Mines, Maanshan, 243000, Anhui (2021-JSKSSYS-04), Any opinions, findings and conclusions are those of the authors and do not necessarily reflect the views of the above agencies.

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Authors and Affiliations

  1. State Key Laboratory of Safety and Health for Metal Mines, Maanshan, 243000, Anhui, People’s Republic of China

    Chunlin Li

  2. College of Power Engineering, Naval University of Engineering, Wuhan, 430033, People’s Republic of China

    Jingjing Guo

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

    Chunlin Li & Youlong Luo

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  1. Jingjing Guo
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  2. Chunlin Li
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Correspondence to Chunlin Li.

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Guo, J., Li, C. & Luo, Y. Resource management and switch migration in SDN-based multi-access edge computing environments. J Supercomput 78, 15532–15566 (2022). https://doi.org/10.1007/s11227-022-04493-5

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