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A Game Theoretic Scheme for Collaborative Vehicular Task Offloading in 5G HetNets.
- Source :
- IEEE Transactions on Vehicular Technology; Dec2020, Vol. 69 Issue 12, p16044-16056, 13p
- Publication Year :
- 2020
-
Abstract
- The 5G heterogeneous networks (HetNets) are capable of providing real-time computing services for autonomous vehicles (AVs) by deploying edge computing devices (ECDs) at macro cell base stations (MCBSs) and small cell base stations (SCBSs). With the imbalanced distribution and fast moving AVs contending intensely for computing services, how to efficiently exploit cooperations among participants in 5G HetNets to improve the service performance is therefore challenging. In this paper, we develop a game theoretic scheme for collaborative vehicular task offloading to facilitate the computing services in 5G HetNets. Specifically, we propose a two-stage vehicular task offloading mechanism to promote the cooperation among participants with the target of improving the task completion rate and the utilities of the participants, where the mechanism jointly considers the network architecture of the HetNets, the imbalanced distribution of AVs and the reuse of task results. In the first stage, an auction model is designed to help the MCBS select the optimal SCBS to execute the offloaded task based on the requirement of the task and the available computing resources of SCBSs. According to the task execution cost declared by the selected SCBS, the MCBS then bargains with the AV for the agreement of the task offloading service to maximize their utilities in the second stage. Using simulations, we show that the proposed collaborative task offloading scheme can achieve a higher task completion rate for the task offloading service and bring higher utilities to all participants than conventional schemes. [ABSTRACT FROM AUTHOR]
- Subjects :
- 5G networks
REAL-time computing
EDGE computing
TASKS
AUTONOMOUS vehicles
Subjects
Details
- Language :
- English
- ISSN :
- 00189545
- Volume :
- 69
- Issue :
- 12
- Database :
- Complementary Index
- Journal :
- IEEE Transactions on Vehicular Technology
- Publication Type :
- Academic Journal
- Accession number :
- 148353672
- Full Text :
- https://doi.org/10.1109/TVT.2020.3041587