Class-based continuous query scheduling for data streams

Authors:
Lory Al Moakar;Thao N. Pham;Panayiotis Neophytou;Panos K. Chrysanthis;Alexandros Labrinidis;Mohamed Sharaf
Affiliations:
University of Pittsburgh;University of Pittsburgh;University of Pittsburgh;University of Pittsburgh;University of Pittsburgh;University of Toronto
Venue:
Proceedings of the Sixth International Workshop on Data Management for Sensor Networks
Year:
2009

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Abstract

Wireless sensor networks link the physical and digital worlds enabling both surveillance as well as scientific exploration. In both cases, on-line detection of interesting events can be accomplished with continuous queries (CQs) in a Data Stream Management System (DSMS). However, the quality-of-service requirements of detecting these events are different for different monitoring applications. The CQs for detecting anomalous events (e.g., fire, flood) have stricter response time requirements over CQs which are for logging and keeping statistical information of physical phenomena. In this work, we are proposing the Continuous Query Class (CQC) scheduler, a new scheduling policy which employs two-level scheduling that is able to handle different ranks of CQ classes. It provides the lowest response times for classes of critical CQs, while at the same time keeping reasonable response times for the other classes down the rank. We have implemented CQC in the AQSIOS prototype DSMS and evaluated it against existing scheduling policies under different workloads.