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Performance research on a task offloading strategy in a two-tier edge structure-based MEC system

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Abstract

With the rapid development for the technology of Mobile edge computing (MEC), tasks tend to be more diversified and personalized, but fewer scholars considered differentiated quality of service requirements from diverse tasks in task offloading studies. In order to guarantee the real-time performance of latency-sensitive tasks and the throughput of latency-tolerant tasks, we propose a task offloading strategy in a MEC system with a two-tier edge structure. We establish a system model composed of a local model and an edge model to capture the workflow of tasks based on our proposed task offloading strategy, and we derive the key performance measures in terms of the average delay of a latency-sensitive task, the average delay of a latency-tolerant task, the utility of MBS Cluster I and the average power of the MEC system. We carry out experiments with analysis and simulation out to evaluate the long-term performance and validate the effectiveness of our proposed task offloading strategy. Finally, by trading off the average delay of a task and the average power of the MEC system, we formulate an optimization problem with inequality constraints for the average delay of a latency-sensitive task and the stability conditions of the MEC system. Furthermore, we develop an improved Powell–Hestenes–Rockafellar algorithm based on Lagrangian multiplier method to jointly optimize the offloading probabilities of the two types of tasks.

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Code availability

The code generated during the current study is available from the corresponding author on reasonable request.

Availability of data and materials

The datasets generated and analyzed during the current study are available from the corresponding author on reasonable request.

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Funding

This work was supported by National Natural Science Foundation (Grant Numbers 62273292, 62276226 and 61973261), China; by the Innovation Capability Improvement Plan Project of Hebei Province (Grant Number 22567626H), China.

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Authors and Affiliations

  1. School of Information Science and Engineering, Yanshan University, West Hebei Avenue, Qinhuangdao, 066004, Hebei, China

    Hao Zhao, Jingwei Geng & Shunfu Jin

  2. The Key Laboratory for Computer Virtual Technology and System Integration of Hebei Province, Yanshan University, West Hebei Avenue, Qinhuangdao, 066004, Hebei, China

    Hao Zhao, Jingwei Geng & Shunfu Jin

Authors
  1. Hao Zhao
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  2. Jingwei Geng
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  3. Shunfu Jin
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Contributions

All authors contributed to the conception and design of the task offloading strategy. HZ established the system model and performed the experiments. JG contributed significantly to the study of related works. SJ contributed to the writing, editing, supervision and funding acquisition.

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Correspondence to Shunfu Jin.

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Zhao, H., Geng, J. & Jin, S. Performance research on a task offloading strategy in a two-tier edge structure-based MEC system. J Supercomput 79, 10139–10177 (2023). https://doi.org/10.1007/s11227-023-05059-9

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