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End-edge-cloud collaborative computation offloading for multiple mobile users in heterogeneous edge-server environment

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Abstract

With the drastic development of Internet of things, the number of connected mobile users (MUs) is increasing at an unprecedented speed. The increasing popularity of MUs has triggered more and more new mobile applications. However, these applications are sensitive to latency, which inevitably increases pressure on MUs. Fortunately, computation offloading of mobile edge computing is becoming a promising technology that can improve quality of service for MUs. However, it becomes much difficult when there are multiple edge servers (ESs) near to the MU, even to the multiple MUs. On the other hand, as the resources of ESs are heterogeneous and finite, and thus it is challenge to design effective offloading strategies for multiple MUs. To tackle the above challenges, we firstly establish a multi-objective optimization model concerning time consumption and energy consumption of MUs, and resource utilization of ESs. Moreover, we devise an end-edge-cloud collaborative computing offloading method based on improved Strength Pareto Evolutionary Algorithm 2 for addressing this mode. Finally, compared to benchmark methods, numerous experiments have proved that our proposed method is effective and efficient and can be widely used for the scenario of multiple MUs and multiple heterogeneous ESs.

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Acknowledgements

The authors thank for the National Science Foundation of China (Grant No. 61902133), the Natural Science Foundation of Fujian Province (Grant No. 2018J05106), the Education and Scientific Research Projects of Young and Middle-aged Teachers in Fujian Province (JZ160084), the Scientific Research Foundation of Huaqiao University under Grant No. 14BS316, and supported by the Fundamental Research Funds for the Central Universities (ZQN-817).

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Authors and Affiliations

  1. College of Engineering, Huaqiao University, Quanzhou, China

    Kai Peng & Hualong Huang

  2. School of Information and Safety Engineering, Zhongnan University of Economics and Law, Wuhan, 430073, China

    Shaohua Wan

  3. Department of Electrical and Computer Engineering, The University of British Columbia, Vancouver, Canada

    Victor C. M. Leung

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  1. Kai Peng
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  2. Hualong Huang
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Contributions

Kai Peng, Hualong Huang, Shaohua Wan, and Victor C.M. Leung conceived and designed the study. Hualong Huang performed the simulations. Kai Peng and Hualong Huang wrote the paper. All authors reviewed and edited the manuscript. All authors read and approved the final manuscript.

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Correspondence to Kai Peng.

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The details of experimental parameters are given in Sect.  5.

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Peng, K., Huang, H., Wan, S. et al. End-edge-cloud collaborative computation offloading for multiple mobile users in heterogeneous edge-server environment. Wireless Netw 30, 3495–3506 (2024). https://doi.org/10.1007/s11276-020-02385-1

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