Article
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Joint Computing Offloading, Task Caching and Resource Allocation Based on TD3 Algorithm in Cache-Assisted Vehicular NOMA-MEC Networks
Version 1
: Received: 10 October 2023 / Approved: 10 October 2023 / Online: 11 October 2023 (14:30:23 CEST)
A peer-reviewed article of this Preprint also exists.
Zhou, T.; Xu, M.; Qin, D.; Nie, X.; Li, X.; Li, C. Computing Offloading Based on TD3 Algorithm in Cache-Assisted Vehicular NOMA–MEC Networks. Sensors 2023, 23, 9064. Zhou, T.; Xu, M.; Qin, D.; Nie, X.; Li, X.; Li, C. Computing Offloading Based on TD3 Algorithm in Cache-Assisted Vehicular NOMA–MEC Networks. Sensors 2023, 23, 9064.
Abstract
In this paper, in order to reduce the energy consumption and delay of data transmission, the non-orthogonal multiple access (NOMA) and edge caching technologies are jointly considered. As for the cache-assisted vehicular NOMA-MEC networks, a problem of minimizing the energy consumed by vehicles (mobile devices, MDs) is formulated under the latency and resource constraints, which jointly optimizes the computing resource allocation, subchannel selection, device association, offloading and caching decisions. To solve the formulated problem, we develop an effective joint computation offloading and task caching algorithm based on the twin delayed deep deterministic policy gradient (TD3) algorithm. Such a TD3-based offloading (TD3O) algorithm includes a designed action transformation (AT) algorithm used for transforming continuous action space into a discrete one. In addition, to solve the formulated problem in a non-iterative manner, an effective heuristic algorithm (HA) is also designed. As for the designed algorithms, we provide some detailed analyses of computation complexity and convergence, and give some meaningful insights through simulation. Simulation results show that the TD3O algorithm may achieve lower local energy consumption than several benchmark algorithms, and HA may achieve a lower one than the completely offloading algorithm and local execution algorithm.
Keywords
TD3; MEC; NOMA; vehicular networks; edge cache; computation offloading; resource allocation
Subject
Computer Science and Mathematics, Artificial Intelligence and Machine Learning
Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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