Low overhead provenance collection partially solves this problem. We propose a data model and collection model for near real time provenance collection. We ...
PDF | Data streams flowing from the physical environment are as unpredictable as the environment itself. Radars go down, long haul net- works drop.
Feb 10, 2006 · Abstract. Data streams flowing from the physical environment are as unpredictable as the environment itself. Radars go down, long haul net-.
Low overhead provenance collection partially solves this problem. We propose a data model and collection model for near real time provenance collection. We ...
Feb 10, 2006 · Abstract. Data streams flowing from the physical environment are as unpredictable as the environment itself. Radars go down, long haul net-.
Towards Low Overhead Provenance Tracking in Near Real-Time Stream Filtering ... Advances and Challenges for Scalable Provenance in Stream Processing Systems.
Low overhead provenance collection partially solves this problem. We propose a data model and collection model for near real time provenance collection. We ...
Towards Low Overhead Provenance Tracking in Near Real-Time Stream Filtering. Author Heading. Nithya N. Vijayakumar · Beth Plale. Publication Date. 2006.
Towards low overhead provenance tracking in near real-time stream filtering. NN Vijayakumar, B Plale. International provenance and annotation workshop, 46-54, ...
Proceedings of the 2006 international conference on Provenance and ...
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May 3, 2006 · Towards low overhead provenance tracking in near real-time stream filtering ... Provenance (JP) service is designed to automate keeping track ...