Enhancing vehicular edge computing system through cooperative computation offloading

Clust. Comput.(2022)

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摘要
Vehicular Edge Computing is the specific application of Mobile Edge Computing in vehicular scenarios. In this work, to efficiently provide on-demand computational resource access for Mission Vehicles, Road Side Units (RSUs) and Cooperative Vehicles are both mounted with edge servers. To further improve the performance of this system, we firstly study the dynamic and cooperative task caching between RSUs. Under the control of the central controller, our caching scheme fully utilizes edge servers’ storage resources. Then, we resort to Deep Deterministic Policy Gradient (DDPG) algorithm to adapt to the time-varying wireless environment. Moreover, we propose the DDPG-OCWB algorithm to improve the convergence performance of DDPG. Finally, numerical results verify the improved performance of our proposed algorithm. Based on a detailed comparison with existing research schemes, it is evident that our scheme dramatically reduces system delay while utilizing edge servers’ energy efficiently.
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关键词
Computation offloading,Task caching,Workload balancing,Vehicular edge Computing
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