Publication Type

Journal Article

Version

Postprint

Publication Date

2-2009

Abstract

In this paper, we present BMQ-Processor, a high-performance Border-Crossing Event (BCE) detection framework for large-scale monitoring applications. We first characterize a new query semantics, namely, Border Monitoring Query (BMQ), which is useful for BCE detection in many monitoring applications. It monitors the values of data streams and reports them only when data streams cross the borders of its range. We then propose BMQ-Processor to efficiently handle a large number of BMQs over a high volume of data streams. BMQ-Processor efficiently processes BMQs in a shared and incremental manner. It develops and operates over a novel stateful query index, achieving a high level of scalability over continuous data updates. Also, it utilizes the locality embedded in data streams and greatly accelerates successive BMQ evaluations. We present data structures and algorithms to support 1D as well as multidimensional BMQs. We show that the semantics of border monitoring can be extended toward more advanced ones and build region transition monitoring as a sample case. Lastly, we demonstrate excellent processing performance and low storage cost of BMQ-Processor through extensive analysis and experiments.

Keywords

Data stream processing, event-based system, stateful query index, BMQ-Index, incremental processing, border monitoring, region transition monitoring, mobile environment, sensor network

Discipline

Software Engineering

Research Areas

Software and Cyber-Physical Systems

Publication

IEEE Transactions on Knowledge and Data Engineering

Volume

21

Issue

2

First Page

234

Last Page

252

ISSN

1041-4347

Identifier

10.1109/TKDE.2008.140

Publisher

IEEE

Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

Additional URL

http://dx.doi.org/10.1109/TKDE.2008.140

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