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Multi-edge collaborative offloading and energy threshold-based task migration in mobile edge computing environment

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Abstract

Computation offloading and service migration are two major research hotspots in the mobile edge computing (MEC) environment. However, in the existing MEC architecture, the idle computing resources of offsite edge servers are not fully utilized, which leads to the problem of high overall system time and energy costs. In this paper, we propose a multi-edge collaborative computation offloading strategy for this problem. The strategy analyzes and calculates the energy consumption and latency cost of task execution for local terminals, edge servers and central cloud, constructs a computation offloading model with the weighted sum of latency and energy consumption as the optimization objective, and then solves the model using an improved genetic algorithm to obtain the best computation offloading decision. On the other hand, the mobility of users in the MEC environment leads to service migration, which leads to unbalanced load on the edge servers and network congestion, etc. This paper proposes an energy threshold-based task migration strategy. The strategy analyzes the time and energy consumption of service execution and data transmission, designs an edge server selection algorithm based on the energy consumption threshold, constructs a service migration model, and finally solves the optimal service migration strategy by improving the genetic algorithm. Experimental results show that the multi-edge collaborative computation offloading strategy proposed can significantly improve the performance of data transfer cost, energy consumption, and task completion time. The proposed migration strategy based on energy consumption threshold can significantly improve the performance of mobile server energy consumption, service completion time, and data transfer energy consumption.

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Acknowledgements

The work was supported by the National Natural Science Foundation (NSF) under grants (No. 62171330, 61873341), Key Research and Development Plan of Hubei Province (No. 2020BAB102), Open project of Key Laboratory of Embedded System and Service Computing (Tongji University), Ministry of Education( No. ESSCKF 2020-5). 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. Key Laboratory of Embedded System and Service Computing (Tongji University), Ministry of Education, Shanghai, 201804, People’s Republic of China

    Chunlin Li

  2. School of Management, Wuhan University of Technology, Wuhan, 430063, People’s Republic of China

    Youlong Luo

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

    Chunlin Li & Qianqian Cai

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  1. Chunlin Li
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Correspondence to Youlong Luo.

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Li, C., Cai, Q. & Luo, Y. Multi-edge collaborative offloading and energy threshold-based task migration in mobile edge computing environment. Wireless Netw 27, 4903–4928 (2021). https://doi.org/10.1007/s11276-021-02776-y

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