A crowd sensing incentive algorithm for data collection for consecutive time slot problems

Crowd sensing (CS) is a new sensing paradigm that takes advantage of the availability of mobile devices almost in every place. In this type of system, the mobile phones users are asked to use their resources such as data plan, energy and time, in order to collect and transmit data to a central infrastructure. Since participants usually do not receive a direct benefit from the system, the incentive mechanisms are required in order to encourage people´s participation in the system. This paper presents a new incentive mechanism for CS based on reverse auctions and the maximization of the variance in the location of selected participants under a budget constraint. The proposed mechanism aims to assure a good coverage of the area of interest as well as the sufficient number of participants in order to guarantee a good quality of information provided to the final user. The experiments present the good performance of the proposed mechanism in terms of number of active participants, budget utilization and coverage of the area of interest.