Quality of Information Aware Incentive Mechanisms for Mobile Crowd Sensing Systems

Recent years have witnessed the emergence of mobile crowd sensing (MCS) systems, which leverage the public crowd equipped with various mobile devices for large scale sensing tasks. In this paper, we study a critical problem in MCS systems, namely, incentivizing user participation. Different from existing work, we incorporate a crucial metric, called users’ quality of information (QoI), into our incentive mechanisms for MCS systems. Due to various factors (e.g., sensor quality, noise, etc.) the quality of the sensory data contributed by individual users varies significantly. Obtaining high quality data with little expense is always the ideal of MCS platforms. Technically, we design incentive mechanisms based on reverse combinatorial auctions. We investigate both the singleminded and multi-minded combinatorial auction models. For the former, we design a truthful, individual rational and computationally efficient mechanism that approximately maximizes the social welfare with a guaran...

• Type: Journal
• Year: 2015
• Where: MOBIHOC
• Authors: Haiming Jin, Lu Su, Danyang Chen, Klara Nahrstedt, Jinhui Xu
• Keywords: Computer Networks, MOBIHOC 2015