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

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 t...

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Vydáno v:IEEE access Ročník 8; s. 52428 - 52442
Hlavní autoři: Wang, Zhen, Zheng, Sifa, Ge, Qiang, Li, Keqiang
Médium: Journal Article
Jazyk:angličtina
Vydáno: Piscataway IEEE 2020
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:
Adaptive systems
Algorithms
Cloud computing
Computation offloading
Computational modeling
Computer & video games
Edge computing
Game theory
intelligent transportation systems
Intelligent vehicles
Numerical analysis
Processor scheduling
Resource allocation
Resource management
Resource scheduling
Scheduling
Servers
Task scheduling
Traffic flow
ISSN:2169-3536, 2169-3536
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Shrnutí: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.
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ISSN:2169-3536
2169-3536
DOI:10.1109/ACCESS.2020.2981045