Cost-sharing models in participatory sensing

Abstract

In Smart City and Participatory Sensing initiatives the key concept is for user communities to contribute sensor information and form a body of knowledge that can be exploited by innovative applications and data analytics services. A key aspect in all such platforms is that sensor information is not free but comes at a cost. As a result, these platforms may suffer due to insufficient sensor information made publicly available if applications do not share efficiently the cost of the sensor information they consume. We explore the design of specialized market mechanisms that match demand to supply while taking into account important positive demand externalities: sensors are digital goods and their cost can be shared by applications. We focus on the buyer side and define different demand models according to the flexibility in choosing sensor data for satisfying application needs. We then investigate the properties of various costsharing mechanisms with respect to efficiency and budget balance. In doing so, we also propose and study a new mechanism, which although lacks strategyproofness, it exhibits important efficiency improvement along with certain fairness properties.