The Cloud Computing Center Performance Analysis Model Based on Queuing Theory

Abstract

Abstract:To make comprehensive and objective analysis of the performance of the cloud computing system center, a cloud computing center system analysis model based on queuing theory is proposed. First, to describe the characteristics of user's service changes request arrived at center by using Poisson distribution, the batch arrival system model was established based on queuing theory, then solve the steady-state probability of length on the probability space, finally to analyze the performance indexes as blocking probability, prompt service probability, etc. by using simulation experiment. The simulation results indicate that with increased batch arrival requests, the average length of the cloud computing center increases correspondingly. Increasing the length of the buffer can reduce the blocking probability of system, the experimental results can provide valuable reference for cloud service providers.