DIFS: a distributed index for features in sensor networks

Sensor networks pose new challenges in the collection and distribution of data. Recently, much attention has been focused on standing queries that use in-network aggregation of time series data to return data statistics in a communication-efficient manner. In this work, rather than consider searches over time series data, we consider searches over semantically rich high-level events, and present the design, analysis, and numerical simulations of a spatially distributed index that provides for efficient index construction and range searches. The scheme provides for a more balanced sharing of communication load over index nodes by using the governing property that the wider the spatial extent known to an index node, the more constrained is the value range covered by that node.