Scale-Up Strategies for Processing High-Rate Data Streams in System S

High performance stream processing is critical in sense-and-respond application domains - from environmental monitoring to algorithmic trading. In this paper, we focus on language and runtime support for improving the performance of sense-and-respond applications in processing data from high rate st...

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Bibliographic Details
Main Authors: Andrade, H., Gedik, B., Kun-Lung Wu, Yu, P.S.
Format: Conference Proceeding
Language:English
Subjects:
Application software
Computer science
Computerized monitoring
Data engineering
Data security
Feeds
Large-scale systems
Middleware
Runtime
Spade
Stock markets
streaming systems
System S
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Summary:High performance stream processing is critical in sense-and-respond application domains - from environmental monitoring to algorithmic trading. In this paper, we focus on language and runtime support for improving the performance of sense-and-respond applications in processing data from high rate streams. The central tenet of this work is the definition of a streaming architectural pattern for these application domains and the programming model and the code generation framework to support it. Using IBM Research's System S middleware and the SPADE language, we demonstrate how to scale up a financial trading application.
ISSN:1063-6382
2375-026X
DOI:10.1109/ICDE.2009.116