Key Performance Information Collection Architecture Based on Cloud Computing

Abstract

Cloud Computing has become another buzzword in recent years. Follow the popular research and use of the cloud system the performance become the bottleneck of the Newborn. More and more researches are turning their attention to analyze the performance of the cloud services. However, it is hard to extract accurate information from the different type of the cloud components such as datacenter, host, Virtual Machines (VM) in the cloud. Thus, it is significant to collect sufficient row data of the Cloud systems for the performance analysis. In this paper, we described an analysis framework to evaluate comprehensive performance guideline of cloud computing center. The analysis architecture is built based on the performance agent and server interface method (PASI), which consists of performance client (PMC), performance agent (PMA) and performance server (PMS), and we put forward a mathematical model based on the PASI information and queuing theory to forecast the idle rate and availability of the cloud environment. It is proved that the PASI architecture is correctly and effectively evaluates the performance of the cloud component and whole cloud environment.