Authors: Themistoklis Palpanas, Dimitris Papadopoulos, Vana Kalogeraki, Dimitrios Gunopulos
Title: Distributed Deviation Detection in Sensor Networks
Conference: SIGMOD Record, Vol 32, No. 4, December 2003
Year: 2003
Abstract: Sensor networks have recently attracted much attention,
because of their potential applications in a number of
different settings. The sensors can be deployed in large
numbers in wide geographical areas, and can be used to
monitor physical phenomena, or to detect certain events.
An interesting problem which has not been adequately
addressed so far is that of distributed online deviation
detection in streaming data. The identification of
deviating values provides an efficient way to focus on the
interesting events in the sensor network.
In this work, we propose a technique for online deviation
detection in streaming data. We discuss how these
techniques can operate efficiently in the distributed environment
of a sensor network, and discuss the tradeoffs
that arise in this setting. Our techniques process as much
of the data as possible in a decentralized fashion, so as
to avoid unnecessary communication and computational
effort.
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