Name
Title | ||
|---|---|---|
Online Offloading Scheduling And Resource Allocation Algorithms For Vehicular Edge Computing System |
Abstract | ||
|---|---|---|
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. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1109/ACCESS.2020.2981045 | IEEE ACCESS |
Keywords | DocType | Volume |
Intelligent vehicles, intelligent transportation systems, edge-computing, game theory | Journal | 8 |
ISSN | Citations | PageRank |
2169-3536 | 0 | 0.34 |
References | Authors | |
0 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Zhen Wang | 1 | 0 | 0.34 |
| Zheng Sifa | 2 | 4 | 2.41 |
| Qiang Ge | 3 | 0 | 0.34 |
| Keqiang Li | 4 | 583 | 52.39 |