Reliable Task Offloading for Vehicular Fog Computing under Information Asymmetry and Information Uncertainty
Author | Zhou Z. |
Author | Liao H. |
Author | Zhao X. |
Author | Ai B. |
Author | Guizani M. |
Available date | 2020-04-23T14:21:33Z |
Publication Date | 2019 |
Publication Name | IEEE Transactions on Vehicular Technology |
Resource | Scopus |
ISSN | 189545 |
Abstract | Vehicular fog computing has emerged as a cost-efficient solution for task processing in vehicular networks. However, how to realize effective server recruitment and reliable task offloading under information asymmetry and uncertainty remains a critical challenge. In this paper, we adopt a two-stage task offloading framework to address this challenge. First, we propose a convex-concave-procedure-based contract optimization algorithm for server recruitment, which aims to maximize the expected utility of the operator with asymmetric information. Then, a low-complexity and stable task offloading mechanism is proposed to minimize the total network delay based on the pricing-based matching. Furthermore, we extend the work to the scenario of information uncertainty and develop a matching-learning-based task offloading mechanism, which takes both occurrence awareness and conflict awareness into consideration. Simulation results demonstrate that the proposed algorithm can effectively motivate resource sharing and guarantee bounded deviation from the optimal performance without the global information. - 2019 IEEE. |
Sponsor | Manuscript received December 31, 2018; revised March 27, 2019; accepted May 7, 2019. Date of publication July 4, 2019; date of current version September 17, 2019. This work was supported in part by Beijing natural Haidian joint fund under Grant L172020, the NSFC under Grants 61601181, 61725101, U1834210, and the Fundamental Research Funds for the Central Universities under Grant 2017MS001. This paper was presented in part at the IEEE International Wireless Communications and Mobile Computing Conference, 2019. The review of this paper was coordinated by the Guest Editors of the Special Section on Vehicle Connectivity and Automation Using 5G. (Corresponding author: Mohsen Guizani.) Z. Zhou, H. Liao, and X. Zhao are with the State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, School of Electrical and Electronic Engineering, North China Electric Power University, Beijing 102206, China (e-mail: zhenyu_zhou@ncepu.edu.cn; haijun_liao@ ncepu.edu.cn; zhaoxw@ncepu.edu.cn). |
Language | en |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Subject | contract theory matching learning pricing-based matching task offloading Vehicular fog computing |
Type | Conference |
Pagination | 8322-8335 |
Issue Number | 9 |
Volume Number | 68 |
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