Monitoring of Grid scientific workflows
Scientific Programming - Large-Scale Programming Tools and Environments
Provenance Querying for End-Users: A Drug Resistance Case Study
ICCS '08 Proceedings of the 8th international conference on Computational Science, Part III
Leveraging complex event processing for grid monitoring
PPAM'09 Proceedings of the 8th international conference on Parallel processing and applied mathematics: Part II
Real-time Grid monitoring based on complex event processing
Future Generation Computer Systems
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Monitoring of running scientific workflows (experiments) is not only important for observing their execution status, but also for collecting provenance, improving performance, knowledge extraction, etc. We propose an ontology model of experiment information which describes the execution of an experiment using a well-defined semantics, and aggregates various aspects of workflow execution including provenance, performance, resource information, and others. Such multi-aspect semantic-rich information is indispensable to build knowledge services on top of it. We describe a grid workflow monitoring architecture which is necessary to collect and correlate workflow monitoring data. The process of aggregation of monitoring data into experiment information is presented. Our approach is validated on a drug resistance ranking application running in the ViroLab virtual labolatory for infectious diseases. Keywords: monitoring, scientific workflows, ontologies