Performance Prediction-based versus Load-based Site Selection: Quantifying the Difference

Distributed systems are available and provide vast compute and data resources to users. With the availability of multiple resources, one of the major issues to be addressed is site selection. Users have access to many resource sites from which to select for execution of applications. In this paper, we quantify the advantages of using performance prediction to select sites as compared to using load information, which is the widely used method. The quantification is based upon two case studies. The first case study involves a large-scale scientific application, called GEO LIGO, for which the experimental results indicate an average of 33% performance improvement as compared to a load-based method. The second case study involves a web-based, educational application, called AADMLSS, for which the results indicate an average of 10% performance improvement as compared to a load-based method.