Energy-efficient data organization and query processing in sensor networks

Authors:
Ramakrishna Gummadi;Xin Li;Ramesh Govindan;Cyrus Shahabi;Wei Hong
Affiliations:
Computer Science Department, University of Southern California, Los Angeles, CA;Computer Science Department, University of Southern California, Los Angeles, CA;Computer Science Department, University of Southern California, Los Angeles, CA;Computer Science Department, University of Southern California, Los Angeles, CA;Intel Research at Berkeley, Berkeley, CA
Venue:
ACM SIGBED Review - Special issue: Best of sensys 2004 work-in-progress
Year:
2005

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Abstract

Recent sensor networks research has produced a class of data storage and query processing techniques called Data-Centric Storage that leverages locality-preserving distributed indexes to efficiently answer multi-dimensional range and range-aggregate queries. These distributed indexes offer a rich design space of a) logical decompositions of sensor relation schema into indexes, as well as b) physical mappings of these indexes onto sensors. In this paper, we discuss this space for energy-efficient data organizations (logical and physical mappings of tuples and attributes to sensor nodes) and examine the performance of purely local query optimization techniques for processing queries that span such decomposed relations.-