Secure-CITI Critical Information-Technology Infrastructure
dg.o '06 Proceedings of the 2006 international conference on Digital government research
Algorithms and metrics for processing multiple heterogeneous continuous queries
ACM Transactions on Database Systems (TODS)
Network Virtualization: A Viable Path Towards the Future Internet
Wireless Personal Communications: An International Journal
Minimizing latency and memory in DSMS: a unified approach to quasi-optimal scheduling
SSPS '08 Proceedings of the 2nd international workshop on Scalable stream processing system
Real-time scheduling for continuous queries with deadlines
Proceedings of the 2009 ACM symposium on Applied Computing
Adaptive scheduling strategy for data stream management system
APWeb/WAIM'07 Proceedings of the joint 9th Asia-Pacific web and 8th international conference on web-age information management conference on Advances in data and web management
A QoS-guaranteeing scheduling algorithm for continuous queries over streams
APWeb/WAIM'07 Proceedings of the joint 9th Asia-Pacific web and 8th international conference on web-age information management conference on Advances in data and web management
Dynamic routing of data stream tuples among parallel query plan running on multi-core processors
Distributed and Parallel Databases
Adaptive online scheduling in storm
Proceedings of the 7th ACM international conference on Distributed event-based systems
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Summary form only given. Data stream management systems are being developed to process continuous queries over multiple data streams. These continuous queries are typically used for monitoring purposes where the detection of an event might trigger a sequence of actions or the execution of a set of specified tasks. Such events are identified by tuples produced by a query and hence, it is important to produce the available portions of a query result as early as possible. A core element for improving the interactive performance of a continuous query is the operator scheduler. An operator scheduler is particularly important when the processing requirements and the productivity of different streams are highly skewed. The need for an operator scheduler becomes even more crucial when tuples from different streams arrive asynchronously. To meet these needs, we are proposing a preemptive rate-based scheduling policy that handles the asynchronous nature of tuple arrival and the heterogeneity in the query plan. Experimental results show the significant improvements provided by our proposed policy.