Realistic Modeling and Synthesis of Resources for Computational Grids

Understanding large Grid platform configurations and generating representative synthetic configurations is critical for Grid computing research. This paper presents an analysis of existing resource configurations and proposes a Grid platform generator that synthesizes realistic configurations of both computing and communication resources. Our key contributions include the development of statistical models for currently deployed resources and using these estimates for modeling the characteristics of future systems. Through the analysis of the configurations of 114 clusters and over 10,000 processors, we identify appropriate distributions for resource configuration parameters in many typical clusters. Using well-established statistical tests, we validate our models against a second resource collection of 191 clusters and over 10,000 processors, and show that our models effectively capture the resource characteristics found in real world resource infrastructures. These models are realized in a resource generator, which can be easily recalibrated by running it on a training sample set.