An Online Incentive Mechanism for Collaborative Task Offloading in Mobile Edge Computing

• Published in: IEEE transactions on wireless communications Vol. 19; no. 1; pp. 624 - 636
• Main Authors: Li, Gang, Cai, Jun
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.01.2020; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Collaboration; collaborative offloading; Computation offloading; Computational modeling; Computer simulation; Delays; Edge computing; MEC; Mobile computing; online mechanism design; Optimization; Resource allocation; Resource management; Servers; Smartphones; social welfare maximization; Task analysis
• ISSN: 1536-1276; 1558-2248
• DOI: 10.1109/TWC.2019.2947046

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.