The coverage problem in a wireless sensor network
WSNA '03 Proceedings of the 2nd ACM international conference on Wireless sensor networks and applications
Probabilistic routing in intermittently connected networks
ACM SIGMOBILE Mobile Computing and Communications Review
Prioritized epidemic routing for opportunistic networks
Proceedings of the 1st international MobiSys workshop on Mobile opportunistic networking
A Delaunay Triangulation based method for wireless sensor network deployment
Computer Communications
Efficient Viewpoint Selection for Urban Texture Documentation
GSN '09 Proceedings of the 3rd International Conference on GeoSensor Networks
Simultaneous placement and scheduling of sensors
IPSN '09 Proceedings of the 2009 International Conference on Information Processing in Sensor Networks
Efficient viewpoint assignment for urban texture documentation
Proceedings of the 17th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems
A case study of participatory data transfer for urban temperature monitoring
W2GIS'11 Proceedings of the 10th international conference on Web and wireless geographical information systems
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The sensing systems that monitor physical environments rely on communication infrastructures (wired or wireless) to collect data from the sensors embedded in the environment. However, in many urban environments pre-existing communication infrastructures are not available, and installing and using new infrastructures is unjustifiably expensive and/or technically infeasible. For such environments, we envision Participatory Data Transfer (PDT) as an alternative communication medium that leverages LBSN (Location Based Social Networks) for data collection. With PDT, LBSN users use their mobile devices to receive data from sensors, and forward the sensed data through the physical network of their mobile devices as well as their connections in the online/virtual social network until the data is received by the data aggregators (data collectors). In this paper, we elaborate on this vision in the context of Quality-aware Participatory Data Transfer (Q-PDT), where PDT must be designed such that it ensures quality guarantees for the sensed data (e.g., sufficiently covering and accurately sensing, timely delivery). In particular, we define and discuss variations of the Q-PDT problem and study its computational complexity.