Energy Efficient Distributed Index for Large Scale Sensor Networks

Sensor networks have opened new horizons and opportunities for a variety of environmental monitoring, surveillance and healthcare applications. One of the major tasks of sensor networks is the distributed collection and processing of sensor readings over extended periods of time. We propose an energyefficient hierarchical indexing approach for spatial data in sensor networks. It allows roaming users to navigate through sensor networks distributed over large geographical areas and to pose spatial queries about the location of the data in the network. One possible application of this approach is related to air pollution monitoring, where sensors with certain pollution levels need to be efficiently located. The major challenge in designing such indexes is the minimization of the total amount of traffic needed to create and maintain the indexes, which is a function of region activity and the actual query rates. Given the dynamic character of the setting, these parameters might in fact change during the network operation, calling for a very adaptive