Research And Implementation Of Elastic Cloud Platform Management And Monitoring System

In order to meet the needs of customers in the Internet environment, service providers need to develop, deploy and maintain the Internet, to reduce the operating costs of the Internet. The emergence of cloud computing is the result of distributed computing, grid computing and parallel computing. Cloud computing environment is composed by a large number of physical servers. When an increase in the number of servers, system administrators rely solely on the experience of performance monitoring and virtual machine scheduling is unreasonable is unrealistic.This paper research on management of elastic cloud platform and cloud monitoring system, the primary tasks are as the follows:(1) Research on performance monitoring data capturing and processing on cloud monitoring system For capturing performance monitoring data, this paper represents complementary push pull algorithm, improving the bandwidth efficiency of the transmission of monitoring data. For processing monitoring data, this paper proposed wavelet neural network prediction algorithm to predict system resource usage and Markov chain algorithm to forecast system fault Both two algorithms provide powerful scheduling decision support for elastic cloud platform management system(2) Design a scheduling algorithm and elastic resource pool management algorithm for elastic cloud platforms. Meanwhile, establish a elastic resource management model for the assessment of the load status of the virtual machine and virtual machine cluster resource utilization. The scheduling algorithm and elastic resource pool management algorithm implement elastic stretching of a single virtual machine instance and virtual machine clusters respectively.(3) Present an elastic cloud management platform. The design of the elastic cloud platform include elastic management platform built using the Open Stack virtualization cluster and implemented in this article. The platform composed by the monitoring module, the Open Stack interface modules, elastic management module, and user interaction module four parts.Finally, the presented platform is deployed and the presented algorithms are verified the feasibility and validated performance. Experiments show that the proposed algorithm is feasible, and validation of the algorithm can be used to improve the efficiency of the cloud platform and resource utilization.