Scoop: An Adaptive Indexing Scheme for Stored Data in Sensor Networks
Author(s)Gil, Thomer M.; Madden, Samuel
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In this paper, we present the design of Scoop, a system for indexing and querying stored data in sensor networks. Scoop works by collecting statistics about the rate of queries and distribution of sensor readings over a sensor network, and uses those statistics to build an index that tells nodes where in the network to store their readings. Using this index, a users queries over that stored data can be answered efficiently, without ﬂooding those queries throughout the network. This approach offers a substantial advantage over other solutions that either store all data externally on a basestation (requiring every reading to be collected from all nodes), or that store all data locally on the node that produced it (requiring queries to be ﬂooded throughout the network). Our results, in fact, show that Scoop offers a factor of four improvement over existing techniques in a real implementation on a 64-node mote-based sensor network. These results also show that Scoop is able to efficciently adapt to changes in the distribution and rates of data and queries.
Massachusetts Institute of Technology Computer Science and Artificial Intelligence Laboratory