A Quality-Aware Reverse Auction-Based Incentive Model for Mobile Crowdsourcing

Mobile crowdsourcing is a promising paradigm where a group of people performs an allocated task requested by a person or an organization. In this mechanism, the task requester can provide the requirements of the contributor with the description of the task. The coordinator calls a reverse auction to select the perfect contributor to complete the task. We propose a reverse auction based incentive mechanism which encourages the contributor to participate in crowdsourcing. We also incentivize the dropout users from the auction with some virtual rewards. This mechanism is computationally efficient, truthful, individually rational and profitable. We also evaluate the performance of the proposed mechanism by conducting several experiments.