Online Offloading Scheduling and Resource Allocation Algorithms for Vehicular Edge Computing System

IEEE Access

Zhen Wang¹  Sifa Zheng¹  Qiang Ge¹  Keqiang Li¹ 

[1] State Key Laboratory of Automotive Safety and Energy, Tsinghua University, Beijing, China;

关键词: Intelligent vehicles;    intelligent transportation systems;    edge-computing;    game theory;   

DOI  :  10.1109/ACCESS.2020.2981045

来源: DOAJ

【 摘 要 】

To accommodate the exponentially increasing computation demands of vehicle-based applications, vehicular edge computing (VEC) system was introduced. This paper considers a three-layer VEC architecture and proposes an online offloading scheduling and resource allocation (OOSRA) algorithm to improve the system performance. Specifically, this study designs a game-theoretic online algorithm to solve the problem of computation task offloading scheduling, and employs an online bin-packing algorithm to compute the resource allocation modified from the First Fit algorithm, which can be adapted to various traffic flow and service attributes. Extensive simulations are conducted, and a numerical analysis of simulation results verifies the effectiveness of the OOSRA-VEC system. The algorithms proposed in this paper are online, adaptive, and distributed, which can provide useful references for future development in VEC system protocols.

【 授权许可】

Unknown