Performance Analysis, Data Sharing, Tools Integration: An Ontology-based Approach
While ontology has widely been applied successfully to represent data in many fields such as AI, Semantic Web, Health, Biology, e.g. see http://www.daml.org/ontologies/category.html, to date such an ontology for performance data in the field performance analysis has yet been developed. Our initial effort is that we try to propose an ontology for representing performance data in the Grid with the hope that the proposed ontology will not only serve for data sharing and reuse between performance analysis tools but also increase the automation of performance analysis process.
In this direction, we are going to develop ontologies based OWL for describing performance metrics and performance data of (Grid) applications. If you think this work is interesting and have free time, joining with us!
- PERFONTO (for performance experiments of parallel programs, see ICCS paper below): Performance experiment ontology and Resource ontology
- WFPERONTO (Performance ontology for Grid workflows, see CCGrid paper below): Download source files from here.
Further information about our research on performance monitoring and analysis themes.
Hong-Linh Truong, Thomas Fahringer, Francesco Nerieri, Schahram Dustd ar,"Performance Metrics and Ontology for Describing Performance Data of Grid Workflows", (PDF), IEEE International Symposium on Cluster Computing and Grid 2005 (CCGrid2005), Grid Performability Workshop, IEEE Computer Society Press, Cardiff, UK, 9 - 12 May 2005. To appear.
Hong-Linh Truong, Thomas Fahringer,"Performance Analysis, Data Sharing and Tools Integration in Grids: New Approach based on Ontology", (PS.GZ, PDF, Slides), International Conference on Computational Science(ICCS 2004), Lecture Notes in Computer Science,(C) Springer-Verlag, Krakow, Poland, June 7-9, 2004.
Hong-Linh Truong, Thomas Fahringer,"An Ontology-based Approach To Performance Analysis, Data Sharing and Tools Integration in Grids", Technical Report AURORATR2004-01 (PS.GZ,PDF), Institute for Software Science, University of Vienna, February, 2004.