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Energy efficient offloading scheme for MEC-based augmented reality system

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Abstract

Augmented reality (AR) is a recent communication paradigm that is considered one of the primary functions of the fifth-generation cellular system (5G). AR is one of the ultra-reliable low latency communications since it requires a total delay of about 5 ms for AR applications. Since mobile devices are battery-operated and have many limitations in computing resources, i.e., processing, storage, and energy, computing tasks associated with mobile AR applications have to be offloaded to nearby devices with sufficient computing resources. To this end, this paper provides a system structure for mobile AR and web-based AR applications; based on the modified multi-level mobile edge computing system (MM-MEC). Furthermore, the required offloading algorithms for managing data offloading from mobile devices to edge servers are introduced. The algorithms are latency and energy-aware, as the selection of the executing device for the AR computing tasks achieves the highest energy and latency efficiency. The proposed structure and offloading techniques have been validated through simulation processes. The developed framework and the proposed offloading schemes have been simulated over a reliable environment for various simulation The suggested system and its offloading methods were simulated in a dependable environment for a number of simulation situations.

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Acknowledgements

The author would like to thank Prince Sultan University for their support.

Funding

The studies at St. Petersburg State University of Telecommunications. prof. M.A. Bonch-Bruevich were supported by the Ministry of Science and High Education of the Russian Federation by the grant 075-15-2022-1137.

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Authors and Affiliations

  1. Department of Electronics and Communications Engineering, Zagazig University, Zagazig, Egypt

    Abdelhamied A. Ateya

  2. Department of Telecommunication Networks and Data Transmission, St. Petersburg State University of Telecommunication, St. Petersburg, Russia

    Abdelhamied A. Ateya, Ammar Muthanna & Andrey Koucheryavy

  3. LaSTI Laboratory, ENSAK, Sultan Moulay Slimane University, Beni-Mellal, Morocco

    Yassine Maleh

  4. EIAS Data Science Lab, College of Computer and Information Sciences, Prince Sultan University, Riyadh, 11586, Saudi Arabia

    Ahmed A. Abd El-Latif

  5. Department of Mathematics and Computer Science, Faculty of Science, Menoufia University, Shebin El-Koom, 32511, Egypt

    Ahmed A. Abd El-Latif

Authors
  1. Abdelhamied A. Ateya
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  2. Ammar Muthanna
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  3. Andrey Koucheryavy
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  4. Yassine Maleh
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  5. Ahmed A. Abd El-Latif
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Correspondence to Ahmed A. Abd El-Latif.

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Ateya, A.A., Muthanna, A., Koucheryavy, A. et al. Energy efficient offloading scheme for MEC-based augmented reality system. Cluster Comput 26, 789–806 (2023). https://doi.org/10.1007/s10586-022-03914-7

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  • DOI: https://doi.org/10.1007/s10586-022-03914-7

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