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. 1

Citations