Scoop: An Adaptive Indexing Scheme for Stored Data in Sensor Networks

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 in a sensor network, and uses those statistics to build an index that tells nodes where in the network to store their data. Using this index, a 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 base station (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 show that Scoop offers a factor of four reduction in message transmissions relative to existing techniques in a real implementation on a 64-node mote-based sensor network. These results also show that Scoop is able to efficiently adapt to changes in the distribution of data and queries.