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|Title:||Leveraging distributed publish/subscribe systems for scalable stream query processing|
|Source:||Zhou, Y.,Tan, K.-L.,Yu, F. (2007). Leveraging distributed publish/subscribe systems for scalable stream query processing. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 4365 LNCS : 20-33. ScholarBank@NUS Repository.|
|Abstract:||Existing distributed publish/subscribe systems (DPSS) offer loosely coupled and easy to deploy content-based stream delivery services to a large number of users. However, the lack of query expressiveness limits their application scope. On the other hand, distributed stream processing engines (DSPE) provide efficient processing services for complex stream queries. Nevertheless, these systems are typically tightly coupled, platform dependent, difficult to deploy and maintain, and less scalable to the number of users. In this paper, we propose a new architectural design for a scalable distributed stream processing system, which provides services to evaluate continuous queries for a large number of clients. It is built by placing a query layer on top of a DPSS architecture. In particular, we focus on solving the query distribution problem in the query layer. © Springer-Verlag Berlin Heidelberg 2007.|
|Source Title:||Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)|
|Appears in Collections:||Staff Publications|
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