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Evaluation of Rate-based Adaptivity in Asynchronous Data Stream Beth Plale and Nithya Vijayakumar

Summary: Evaluation of Rate-based Adaptivity in Asynchronous Data Stream
Beth Plale and Nithya Vijayakumar
Computer Science Department
Indiana University
Continuous query systems are an intuitive way for users
to access streaming data in large-scale scientific applica-
tions containing many hundreds of streams. A challenge
in these systems is to join streams in such a way that mem-
ory is conserved. Storing events that could not possibly
participate in a join any longer wastes memory and limits
scalability of the query processing system. This paper re-
ports an experiment we conducted to validate an algorithm
we developed for adaptive rate, adjustable join windows.
We posit that a rate-based strategy can result in memory
savings, can be sufficiently responsive to rapid changes
in stream rates, and can execute with suitably low over-
head. Based on the results, we conclude that the algorithm
adds between 0.007% and 2.6% overhead, with significant




Collections: Computer Technologies and Information Sciences