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An Online Incentive Mechanism for Collaborative Task Offloading in Mobile Edge Computing
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DOI：10.1109/TWC.2019.2947046.png)
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摘要
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This paper discusses incentive mechanism design for collaborative task offloading in mobile edge computing (MEC). Different from most existing work in the literature that was based on offline settings, in this paper, an online truthful mechanism integrating computation and communication resource allocation is proposed. In our system model, upon the arrival of a smartphone user who requests task offloading, the base station (BS) needs to make a decision right away without knowing any future information on i) whether to accept or reject this task offloading request and ii) if accepted, who to execute the task (the BS itself or nearby smartphone users called collaborators). By considering each task's specific requirements in terms of data size, delay, and preference, we formulate a social-welfare-maximization problem, which integrates collaborator selection, communication and computation resource allocation, transmission and computation time scheduling, as well as pricing policy design. To solve this complicated problem, a novel online mechanism is proposed based on the primal-dual optimization framework. Theoretical analyses show that our mechanism can guarantee feasibility, truthfulness, and computational efficiency (competitive ratio of 3). We further use comprehensive simulations to validate our analyses and the properties of our proposed mechanism.
Keyword:
Task analysis
Collaboration
Resource management
Servers
Computational modeling
Optimization
Delays
MEC
collaborative offloading
online mechanism design
social welfare maximization
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期刊
IF:
10.7
论文数:
1.3W
被引数:
5.3W
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