A location-based incentive mechanism for participatory sensing systems with budget constraints

TLDR

Participatory sensing systems depend on mobile users’ willingness to collect and report data, but lack of incentives has limited their success. This work proposes an incentive scheme that incorporates location information while respecting budget and coverage constraints to make participation more realistic and efficient. The scheme is a recurrent reverse auction that uses a greedy algorithm to select a representative subset of users based on location within a fixed budget. Compared to existing mechanisms, it increases area coverage by over 60 % and yields a more representative sample each round while keeping the same number of active users and budget.

Abstract

Participatory sensing (PS) systems rely on the willingness of mobile users to participate in the collection and reporting of data using a variety of sensors either embedded or integrated in their cellular phones. However, this new data collection paradigm has not been very successful yet mainly because of the lack of incentives for participation. Although several incentive schemes have been proposed to encourage user participation, none has used location information and imposed budget and coverage constraints, which will make the scheme more realistic and efficient. We propose a recurrent reverse auction incentive mechanism with a greedy algorithm that selects a representative subset of the users according to their location given a fixed budget. Compared to existing mechanisms, our incentive scheme improves the area covered by more than 60 percent acquiring a more representative set of samples after every round while maintaining the same number of active users in the system and spending the same budget.