On Opportunistic Coverage for Urban Sensing

Dong Zhao, Huadong Ma, Liang Liu, Jing Zhao

Abstract: Opportunistic sensing is a new paradigm which exploits human-carried or vehicle-mounted sensors to collect data ubiquitously for large-scale urban sensing. Existing work lacks an in-depth investigation on the sensing quality of such sensing systems, which faces two basic problems: 1) how to measure the sensing quality? and 2) how many humans or vehicles are necessary to satisfy the sensing quality requirement of the whole urban area? To solve the first problem, we propose a metric called Inter-Cover Time (ICT) to characterize the opportunity with which a sub region is covered, which reflects the sensing quality directly. According to the empirical measurement studies on real mobility traces of thousands of taxis collected in Beijing and Shanghai, we find that the aggregated ICT Distribution (ICTD) closely resembles a truncated power-law distribution regardless of the size of sub regions and the number of vehicles. We also analyze the reasons behind this particular pattern by the evaluation on four known mobility models. To solve the second problem, we further propose a metric called opportunistic coverage ratio based on the ICTD to characterize the relationship between the sensing quality of an urban area and vehicle number. Our results provide fundamental guidelines on the measurement of sensing quality and network planning for opportunistic urban sensing applications.