Performance evaluation and analysis of SEU Cloud Computing Platform — Using general benchmarks and real world AMS application

Abstract

Cloud computing, as a popular technique to support and achieve CSCW, is gaining increasing importance in recent years, where the virtualization becomes the key technique. However, although utilizing virtualization can implement more efficient and flexible resource allocation, it may also come at the cost of increased system complexity and dynamics. In order to effectively adapt to performance fluctuations for ensuring high-performance, a generic approach to predict the performance influences of cloud platforms is highly desirable. To address this request, in this paper, the major factors that affect the performance of cloud and the relevant variation discipline are evaluated and analyzed thoroughly using a series of benchmarks in SEU (Southeast University) Cloud Computing Platform, where not only a general methodology on quantifying the performance influence but also the most important impact factors are proposed. Moreover, we use a real world application, as AMS experiment, to further evaluate the relevant performance.