5G MEC-based intelligent computation offloading in power robotic inspection

Wang, W., Qu, R., Liao, H., Wang, Z., Zhou, Z., Wang, Z., Mumtaz, S. ORCID: 0000-0001-6364-6149 and Guizani, M., 2023. 5G MEC-based intelligent computation offloading in power robotic inspection. IEEE Wireless Communications, 30 (2), pp. 66-74. ISSN 1536-1284

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Power robotic inspection plays a critical role in the realization of real-time visualization and perception of substation in power grid. 5G mobile edge computing (MEC) has emerged as a promising solution to provide the large bandwidth, wide connectivity, and proximate computing capabilities for the computation offloading of power robotic inspection with stringent delay requirements. This article proposes a 5G MEC-based intelligent computation offloading framework in power robotic inspection to cope with multi-dimension entity heterogeneity, environment dynamics, and inspection delay guarantee. Specifically, the proposed framework and the implementation procedures of computation offloading are firstly elaborated, and the research challenges are outlined. Then, we propose an artificial intelligence (AI)-enabled multi-dimension collaborative optimization algorithm of route planning and task offloading to address the low-latency computation offloading problem under queue stability constraint. A case study is provided to verify the superiority of delay and queue backlog performance through simulation results.

Item Type: Journal article
Publication Title: IEEE Wireless Communications
Creators: Wang, W., Qu, R., Liao, H., Wang, Z., Zhou, Z., Wang, Z., Mumtaz, S. and Guizani, M.
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: April 2023
Volume: 30
Number: 2
ISSN: 1536-1284
Rights: © 2023 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Divisions: Schools > School of Science and Technology
Record created by: Laura Ward
Date Added: 10 May 2023 15:52
Last Modified: 10 May 2023 15:52
URI: https://irep.ntu.ac.uk/id/eprint/48922

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