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Offloading strategy with PSO for mobile edge computing based on cache mechanism

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Abstract

With the development of Internet of Things (IoT) devices and the growth of users’ demand for computation and real-time services, artificial intelligence has been applied to reduce the system cost for future network systems. To meet the demand of network services, the paradigm of edge networks is increasingly shifting towards the joint design of computation, communication and caching services. This paper investigates a multi-user cache-enabled mobile edge computing (MEC) network and proposes an intelligent particle swarm optimization (PSO) based offloading strategy with cache mechanism. In each time slot, the server selects one file among multiple ones to pre-store, according to the proposed cache replacement strategy. In the next time slot, the requested files by the users needn’t to be computed and offloaded, if these files have been cached in the server. For the files that have not been cached in the server, PSO algorithm is adopted to find an appropriate offloading ratio to implement the partial offloading. Simulation results are finally presented to validate the proposed studies. In particular, we can find that incorporating the proposed cache replacement strategy into the computation offloading can effectively reduce the system latency and energy consumption for the future networks.

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Data availability

The authors state the data availability in this manuscript.

Code availability

Not applicable.

Abbreviations

MEC:

Mobile edge computing

BSs:

Base stations

PSO:

Particle swarm optimization

UAV:

Unmanned aerial vehicle

ES:

Edge server

FIFO:

First in first out

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Acknowledgements

This work was supported in part by the International Science and Technology Cooperation Projects of Guangdong Province (No. 2020A0505100060), Natural Science Foundation of Guangdong Province (Nos. 2021A1515011392/2021A1515011812), and in part by the research program of Guangzhou University (No. YK2020008/YJ2021003).

Funding

This work was supported in part by the International Science and Technology Cooperation Projects of Guangdong Province (No. 2020A0505100060), Natural Science Foundation of Guangdong Province (Nos. 2021A1515011392/2021A1515011812), and in part by the research program of Guangzhou University (No. YK2020008/YJ2021003).

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Authors and Affiliations

  1. School of Computer Science, Guangzhou University, Guangzhou, China

    Wenqi Zhou, Shunpu Tang, Lijia Lai, Junjuan Xia & Liseng Fan

  2. School of Electronics and Communication Engineering, Guangzhou University, Guangzhou, China

    Lunyuan Chen & Fasheng Zhou

Authors
  1. Wenqi Zhou
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  2. Lunyuan Chen
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  3. Shunpu Tang
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  4. Lijia Lai
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  5. Junjuan Xia
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  6. Fasheng Zhou
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  7. Liseng Fan
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Contributions

WZ designed the proposed offloading and caching strategy. LC helped conduct the simulation and verify the results. ST, LL and JX analyzed the application scenarios of the model, arranged the data, and proof read this paper. FZ was responsible for the check of the full paper and simulations. LF was responsible for checking the critical steps in the strategy design and improving the presentation style of the whole paper. All authors read and approved the final manuscript.

Corresponding authors

Correspondence to Fasheng Zhou or Liseng Fan.

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Zhou, W., Chen, L., Tang, S. et al. Offloading strategy with PSO for mobile edge computing based on cache mechanism. Cluster Comput 25, 2389–2401 (2022). https://doi.org/10.1007/s10586-021-03414-0

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  • DOI: https://doi.org/10.1007/s10586-021-03414-0

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