A novel incentive negotiation mechanism for participatory sensing under budget constraints

Incentive allocation is an important research issue in participatory sensing as it determines the willingness of participants in joining the sensing campaign. Existing incentive approaches either decide the payments without consulting the participants, or require burdensome negotiation procedures like bid-price auction. In this paper, we propose a novel incentive allocation mechanism, which encourages participation and allocates incentives dynamically to achieve accurate sensing results. The proposed mechanism consists of two major elements. The first is a lightweight incentive negotiation procedure, which dynamically offers incentives to participants in spatio-temporal subregions and collects their responses. The second is the optimization problem for incentive allocation as well as it's solution, which aims at maximizing data quality by capturing the amount and the distribution of data samples. Simulations with real datasets confirmed that the proposed solution can provide dynamic incentive offers according to the estimated value of participants' data contribution to the overall quality of sensing result.