Online Incentive Mechanism Design for Real-Time Decision Making: Case Study of Collaborative Task Offloading in Mobile Edge Computing

In Chap. 3 , a nonlinear online incentive mechanism for task offloading under Internet of Things (IoT) scenario was introduced. while the I̲ntegrate R̲ounding S̲cheme based M̲IDR (IRSM) framework was elaborated to demonstrate the design for the considered scenario, it is applicable for time-slotted cases only. In this chapter, a real-time decision making online incentive mechanism designs is elucidated under a collaborative task offloading case in EC. In the considered system model, upon the arrival of a requester, it submits its private information to the central controller (i.e., the BS) to request a task offloading. After receiving the request, the BS makes decisions right away on task executor selection, time scheduling, resource allocation, and reward determination. With the objective of maximizing the total social welfare, we formulate a complex optimization problem and design a real-time decision making online incentive mechanism based on the primal-dual framework. Finally, theoretical analyses show that our mechanism can guarantee feasibility, truthfulness, and computational efficiency (competitive ratio of 3).