Encapsulation of parallelism in the Volcano query processing system
SIGMOD '90 Proceedings of the 1990 ACM SIGMOD international conference on Management of data
Continuous queries over append-only databases
SIGMOD '92 Proceedings of the 1992 ACM SIGMOD international conference on Management of data
Query evaluation techniques for large databases
ACM Computing Surveys (CSUR)
Hancock: a language for extracting signatures from data streams
Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining
The state of the art in distributed query processing
ACM Computing Surveys (CSUR)
Models and issues in data stream systems
Proceedings of the twenty-first ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Continual Queries for Internet Scale Event-Driven Information Delivery
IEEE Transactions on Knowledge and Data Engineering
The Tangram Stream Query Processing System
Proceedings of the Fifth International Conference on Data Engineering
SVP: A Model Capturing Sets, Lists, Streams, and Parallelism
VLDB '92 Proceedings of the 18th International Conference on Very Large Data Bases
Gigascope: a stream database for network applications
Proceedings of the 2003 ACM SIGMOD international conference on Management of data
Monitoring streams: a new class of data management applications
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
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Today many current and emerging applications require support for on-line analysis of rapidly changing data streams. Limitations of traditional DBMSs in supporting streaming applications have been recognized, prompting research to augment existing technologies and build new systems to manage streaming data. Stream-oriented systems are inherently geographically distributed and because distribution offers scalable load management and higher availability, future stream processing systems will operate in a distributed fashion. Moreover, service-based approaches have gained considerable attention recently for supporting distributed application development in e-business and e-science. In this paper, we present our innovative work to build a large scale distributed query processing over streaming data, this system has been designed as a WSRF-compliant application built on top of standard Web services technologies. Our distributed data stream Queries are written and evaluated over distributed resources discovered and accessed using emerging the WS-Resource Framework specifications. The data stream query processor has been designed and implemented as a collection of cooperating services, using the facilities of the WSRF to dynamically discover, access and use computational resources to support query compilation and evaluation.