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Resource Allocation for Edge Computing-Based Vehicle Platoon on Freeway: A Contract-Optimization Approach.
- Source :
-
IEEE Transactions on Vehicular Technology . Dec2020, Vol. 69 Issue 12, p15988-16000. 13p. - Publication Year :
- 2021
-
Abstract
- Vehicular edge computing is viewed as a promising technique for relieving the overload of base station (BS) on roadside, via leveraging the computation resources of vehicles on road. However, the computing capacity of a single vehicle is limited. For the fast velocity and distribution characteristics of vehicles, when a vehicle performs task offloading to a set of neighbor vehicles, longer sensing/accessing time durations are needed. Vehicle platoon driving as an emerging technique is proposed to strengthen vehicle fuel efficiency and the freeway safety and capacity. The distributed computation resources can be centrally controlled in the vehicle platoon. In this paper, we investigate the resource allocation scheme for edge computing-based vehicle platoon on freeway to maximize the utilities of vehicles surrounding the platoon via a contract-optimization approach. Combining with BS, the vehicle platoon performs as an edge node to provide the delay-sensitive computation service for the vehicles on road. First, we design a contract-based incentive mechanism to motivate vehicles to form a vehicle platoon and share their computation resources. Then, based on the proposed vehicle platoon, a joint optimization problem is formulated to maximize the utilities of vehicles, the task offloading decision, communication and computation resource allocation schemes in both the platoon and BS are jointly optimized. Numerical results reveal that the designed contracts can incentivize vehicle's participation, and the proposed resource allocation schemes are effective. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 00189545
- Volume :
- 69
- Issue :
- 12
- Database :
- Academic Search Index
- Journal :
- IEEE Transactions on Vehicular Technology
- Publication Type :
- Academic Journal
- Accession number :
- 148381140
- Full Text :
- https://doi.org/10.1109/TVT.2020.3039851