Online Incentive Mechanism for Mobile Crowdsourcing Based on Two-Tiered Social Crowdsourcing Architecture

Abstract

Mobile crowdsourcing has become an efficient paradigm for performing large scale tasks. The incentive mechanism is important for the mobile crowdsourcing system to stimulate participants, and to achieve good service quality. In this paper, we focus on solving the insufficient participation problem in the budget constrained online crowdsourcing system. We present a two-tiered social crowdsourcing architecture, which can enable the selected registered users to recruit their social neighbors by diffusing the tasks to their social circles. In the two-tiered social crowdsourcing system, the tasks are associated with different end times, and both the registered users and their social neighbors have different arrival/departure times. An online incentive mechanism, MTSC, which consists of two steps: Agent Selection and Online Reverse Auction, is proposed for this novel mobile crowdsourcing system. Through both rigorous theoretical analysis and extensive simulations, we demonstrate that the proposed incentive mechanism achieves computational efficiency, individual rationality, budget feasibility, cost truthfulness, and time truthfulness.