An Energy Efficiency Analysis of Computation Offloading in MEC-Enabled IoV Networks

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An Energy Efficiency Analysis of Computation Offloading in MEC-Enabled IoV Networks
Title:
An Energy Efficiency Analysis of Computation Offloading in MEC-Enabled IoV Networks
Journal Title:
2023 IEEE 97th Vehicular Technology Conference (VTC2023-Spring)
Keywords:
Publication Date:
14 September 2023
Citation:
Hui Ernest, T. Z., & Madhukumar, A. S. (2023, June). An Energy Efficiency Analysis of Computation Offloading in MEC-Enabled IoV Networks. 2023 IEEE 97th Vehicular Technology Conference (VTC2023-Spring). https://doi.org/10.1109/vtc2023-spring57618.2023.10201046
Abstract:
The average energy efficiency of computation offloading in multi-access edge computing (MEC) enabled Internet-of-Vehicles (IoV) networks with wired backhaul links is investigated in this paper. Specifically, the cumulative distribution function (CDF) for computation delay over wired backhaul link is derived in closed-form. The average energy efficiency of computation offloading in MEC-enabled IoV networks with wired backhaul links is derived in closed-form, and is compared against non MEC-enabled IoV networks with wired backhaul links. Numerical and simulation results show that MEC-enabled IoV networks can attain at least 10 times higher energy efficiency than non MEC-enabled IoV networks. Furthermore, we show that energy efficiency can be maximized through the proper selection of task size and transmission deadline in the MEC-enabled IoV network.
License type:
Publisher Copyright
Funding Info:
This research is supported by core funding from: A*STAR Advanced Remanufacturing and Technology Centre (ARTC)
Grant Reference no. : N/A
Description:
© 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.
ISSN:
2577-2465
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