Encyclopedia of Database Systems

2018 Edition
| Editors: Ling Liu, M. Tamer Özsu

Scheduling Strategies for Data Stream Processing

  • Mohamed SharafEmail author
  • Alexandros Labrinidis
Reference work entry
DOI: https://doi.org/10.1007/978-1-4614-8265-9_321


Continuous query scheduling; Operator scheduling; Scheduling policies


In a Data Stream Management System (DSMS), data arrives in the form of continuous streams from different data sources, where the arrival of new data triggers the execution of multiple continuous queries (CQs). The order in which CQs are executed in response to the arrival of new data is determined by the CQ scheduler. Thus, one of the main goals in the design of a DSMS is the development of scheduling policies that leverage CQ characteristics to optimize the DSMS performance.

Historical Background

The growing need for monitoring applications [8] has forced an evolution on data processing paradigms, moving from Database Management Systems (DBMSs) to Data Stream Management Systems (DSMSs) [4, 11]. Traditional DBMSs employ a store-and-then-query data processing paradigm, where data are stored in the database and queries are submitted by the users to be answered in full, based on the current snapshot...

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Electrical and Computer EngineeringUniversity of TorontoTorontoCanada
  2. 2.Department of Computer ScienceUniversity of PittsburghPittsburghUSA

Section editors and affiliations

  • Uĝur Çetintemel
    • 1
  1. 1.Brown UniversityProvidenceUSA