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Continuous queries over append-only databases
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Performing data flow testing on classes
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VisAD: connecting people to computations and people to people
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Eddies: continuously adaptive query processing
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Design and evaluation of a wide-area event notification service
ACM Transactions on Computer Systems (TOCS)
Applying scheduling and tuning to on-line parallel tomography
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Accurate estimation of the number of tuples satisfying a condition
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Continuous queries over data streams
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Continual Queries for Internet Scale Event-Driven Information Delivery
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Event Services for High Performance Computing
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dQUOB: Managing Large Data Flows Using Dynamic Embedded Queries
HPDC '00 Proceedings of the 9th IEEE International Symposium on High Performance Distributed Computing
2K: A Distributed Operating System for Dynamic Heterogeneous Environments
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Dynamic Monitoring of High-Performance Distributed Applications
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Software Approach To Hazard Detection Using On-Line Analysis Of Safety Constraints
SRDS '97 Proceedings of the 16th Symposium on Reliable Distributed Systems
SS '95 Proceedings of the 28th Annual Simulation Symposium
ACDS: Adapting Computational Data Streams for High Performance
IPDPS '00 Proceedings of the 14th International Symposium on Parallel and Distributed Processing
Fjording the Stream: An Architecture for Queries Over Streaming Sensor Data
ICDE '02 Proceedings of the 18th International Conference on Data Engineering
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ICDCS '99 Proceedings of the 19th IEEE International Conference on Distributed Computing Systems
Run-time Detection in Parallel and Distributed Systems: Application to Safety-Critical Systems
ICDCS '99 Proceedings of the 19th IEEE International Conference on Distributed Computing Systems
Resource allocation in a middleware for streaming data
MGC '04 Proceedings of the 2nd workshop on Middleware for grid computing
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Supporting fault-tolerance in streaming grid applications
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Scientific Programming - AxGrids 2004
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Improving data analysis through diverse data source integration
MILCOM'09 Proceedings of the 28th IEEE conference on Military communications
Resource allocation for multiple concurrent in-network stream-processing applications
Euro-Par'09 Proceedings of the 2009 international conference on Parallel processing
Supporting self-adaptation in streaming data mining applications
IPDPS'06 Proceedings of the 20th international conference on Parallel and distributed processing
Efficient in-network evaluation of multiple queries
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A data stream publish/subscribe architecture with self-adapting queries
OTM'05 Proceedings of the 2005 Confederated international conference on On the Move to Meaningful Internet Systems - Volume >Part I
Stream integration techniques for grid monitoring
Journal on Data Semantics II
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IPAW'06 Proceedings of the 2006 international conference on Provenance and Annotation of Data
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Data streaming has established itself as a viable communication abstraction in data-intensive parallel and distributed computations, occurring in applications such as scientific visualization, performance monitoring, and large-scale data transfer. A known problem in large-scale event communication is tailoring the data received at the consumer. It is the general problem of extracting data of interest from a data source, a problem that the database community has successfully addressed with SQL queries, a time tested, user-friendly way for noncomputer scientists to access data. By leveraging the efficiency of query processing provided by relational queries, the dQUOB system provides a conceptual relational data model and SQL query access over streaming data. Queries can be used to extract data, combine streams, and create new streams. The language augments queries with an action to enable more complex data transformations such as Fourier transforms. The dQUOB system has been applied to two large-scale distributed applications: a safety critical autonomous robotics simulation and scientific software visualization for global atmospheric transport modeling. In this paper, we present the dQUOB system and the results of performance evaluation undertaken to assess its applicability in data-intensive wide-area computations, where the benefit of portable data transformation must be evaluated against the cost of continuous query evaluation.