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Computation Offloading Algorithm for Arbitrarily Divisible Applications in Mobile Edge Computing Environments: An OCR Case

Author

Listed:
  • Bo Li

    (School of Information Science and Engineering, Yunnan University, Kunming 650091, China)

  • Min He

    (School of Information Science and Engineering, Yunnan University, Kunming 650091, China)

  • Wei Wu

    (College of Electronics and Information Engineering, Sichuan University, Chengdu 610065, China)

  • Arun Kumar Sangaiah

    (School of Computing Science and Engineering, Vellore Institute of Technology (VIT), Vellore 632014, India)

  • Gwanggil Jeon

    (Department of Embedded Systems Engineering, Incheon National University, Incheon 22012, Korea)

Abstract

Divisible applications are a class of tasks whose loads can be partitioned into some smaller fractions, and each part can be executed independently by a processor. A wide variety of divisible applications have been found in the area of parallel and distributed processing. This paper addresses the problem of how to partition and allocate divisible applications to available resources in mobile edge computing environments with the aim of minimizing the completion time of the applications. A theoretical model was proposed for partitioning an entire divisible application according to the load of the application and the capabilities of available resources, and the solutions were derived in closed form. Both simulations and real experiments were carried out to justify this model.

Suggested Citation

  • Bo Li & Min He & Wei Wu & Arun Kumar Sangaiah & Gwanggil Jeon, 2018. "Computation Offloading Algorithm for Arbitrarily Divisible Applications in Mobile Edge Computing Environments: An OCR Case," Sustainability, MDPI, vol. 10(5), pages 1-14, May.
  • Handle: RePEc:gam:jsusta:v:10:y:2018:i:5:p:1611-:d:146911
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    Cited by:

    1. Mohamed Elhoseny & Mohammad Siraj & Khalid Haseeb & Muhammad Nawaz & Majid Altamimi & Mohammed I. Alghamdi, 2022. "Energy-Efficient Mobile Agent Protocol for Secure IoT Sustainable Applications," Sustainability, MDPI, vol. 14(14), pages 1-13, July.
    2. Yousaf Bin Zikria & Sung Won Kim & Muhammad Khalil Afzal & Haoxiang Wang & Mubashir Husain Rehmani, 2018. "5G Mobile Services and Scenarios: Challenges and Solutions," Sustainability, MDPI, vol. 10(10), pages 1-9, October.

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