Efficiency Model of Intelligent Cloud Based on BP Neural Network

Abstract

Recently,we are facing the increasingly large and complex intelligent applications in cloud computing.Establishing an effective quality model of cloud service is an important methodology to evaluate cloud service quality.However,due to the diversity and dynamic characteristics of intelligent cloud resources,it is very difficult to evaluate the service efficiency of intelligent cloud.At present,there is a lack of standard and unified cloud service quality evaluation and cloud service model in the field of intelligent cloud computing.In this paper,the abstract service quality of intelligent cloud is embodied as cloud service efficiency,and cloud service efficiency is defined as the service availability,reliability and performance reflecting service efficiency.That is to quantitatively evaluate the overall service capability of intelligent cloud through the output of cloud service efficiency.Moreover,this paper proposes an efficiency model of intelligent cloud based on BP neural network.The complex nonlinear relationship between input characteristics and output service efficiency of intelligent cloud is simulated by BP neural network.Once the input characteristics are determined,the output service efficiency can be computed.The efficiency model is responsible for predicting the service level of the current system in real time according to the input characteristics of the system accurately.The experimental results show that the BP neural network model,as a modeling tool of service efficiency model,has good computing efficiency and accuracy.

Keywords

• bp neural network|intelligent cloud|efficiency model|service efficiency|input characteristics