Several emerging wireless sensor network applications must cope with a combination of node mobility (e.g., sensors on moving cars) and high data rates (media-rich sensors capturing videos, images, sounds, etc.). Due to their mobility, these sensor networks display intermittent and variable network connectivity, and often have to deliver large quantities of data relative to the bandwidth available during periods of connectivity. Unfortunately, existing distributed data management and stream processing are not appropriate for such applications because they assume that the network connecting nodes in the data processor is "always on," and that the absence of a network connection is a fault that needs to be masked to avoid failure. This thesis describes ICEDB (Intermittently Connected Embedded Database), a continuous query processing system for intermittently connected mobile sensor networks. ICEDB incorporates two key ideas: (1) a delay-tolerant continuous query processor, coordinated by a central server and distributed across the mobile nodes, and (2) algorithms for prioritizing certain query results to improve application-defined "utility" metrics. We describe the results of several experiments that use data collected from a deployed fleet of cabs driving in Boston.
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