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A Review of Computational Load-Balancing for Mobile Edge Computing

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Intelligent Computing (SAI 2023)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 711))

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Abstract

Living and working smarter is becoming the new trend, and this is primarily made possible by the growth in the number of connected internet of things (IoT) devices globally. IoT’s foremost challenges include energy challenges and their inability to meet the latency demands of user applications. These are somewhat connected to their over-dependence on cloud services for data processing. In recent years, edge computing variants have been considered for a shift from IoT applications’ dependence on traditional cloud for data processing. However, the compute resources of individual edge devices are woefully inadequate. Hence, the need for efficient offloading strategies and resource allocation algorithms that will distribute and balance computational tasks among several collaborating edge servers/devices. Different algorithms, including Heuristic algorithms, Machine Learning techniques, Bio-inspired and Genetic algorithms and Game theory-based approaches, have been studied by researchers towards optimizing computational load balancing in edge computing solutions. This paper systematically reviews the adaptation of Mobile Edge Computing for latency improvement in IoT applications with a specific focus on state-of-the-art computational load balancing and offloading strategies. The paper further outlines future research directions and open issues that researchers can explore to find solutions to the latency gap in using Mobile Edge Computing for IoT data processing.

H. Nunoo-Mensah and K. Osei Boateng—These authors contributed equally to this work.

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Authors and Affiliations

  1. Department of Computer Engineering, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana

    Michael Wilson, Henry Nunoo-Mensah & Kwame Osei Boateng

  2. Institute for Scientific and Technological Information, Council for Scientific and Industrial Research (CSIR), Accra, Ghana

    Michael Wilson

  3. Connected Devices Lab, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana

    Henry Nunoo-Mensah & Kwame Osei Boateng

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  1. Michael Wilson
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  1. Faculty of Science and Engineering, Saga University, Saga, Japan

    Kohei Arai

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Wilson, M., Nunoo-Mensah, H., Boateng, K.O. (2023). A Review of Computational Load-Balancing for Mobile Edge Computing. In: Arai, K. (eds) Intelligent Computing. SAI 2023. Lecture Notes in Networks and Systems, vol 711. Springer, Cham. https://doi.org/10.1007/978-3-031-37717-4_7

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