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Research and Application of Monitoring System for Cloud Computing Platform

Author: ZhangQiSheng
Tutor: WangYiZhi
School: Beijing Jiaotong University
Course: Computer Science and Technology
Keywords: Cloud computing platform Cluster Monitoring Prediction model Service levels Hadoop Virtual Machine
CLC: TP277
Type: Master's thesis
Year: 2011
Downloads: 639
Quote: 3
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Abstract


Cloud computing platform with a virtual , hierarchical and dynamic characteristics , compared to grid computing is more complex . Monitoring is an important part of the cloud computing platform , play an important role in improving the quality of service of the cloud computing platform . Therefore, the cloud computing platform monitoring system has important significance. Firstly, the existing monitoring system data acquisition , combined with the current widespread use of push and pull mode , the advantages of designing a push-pull hybrid data acquisition algorithm to improve the collection efficiency . The experimental results show that the algorithm is able to reduce the number of acquisitions , reducing the system 's intervention . For real - time monitoring system data processing lag issues , then design a behavior-based learning model for predicting the future performance of the system . The prediction model is subdivided according to the characteristics of cloud computing platform for the monitoring data and the need to predict the time range for the long - term performance data , the short-term threshold cross-border as well as accident early prediction model . The combination of data mining , machine learning technology , the design model algorithm . In addition , use of the prediction model accuracy assessment equation , the study forecast model dynamic adaptability . Finally, the combination of the characteristics of the cloud computing platform , and to simplify the complexity of the system , abstraction levels and scalability of cloud computing platform component model . Then , from the aspects of scalability , low coupling , timeliness, accuracy , low intervention and versatility to consider the design and implementation of the monitoring system . At the same time , to verify the feasibility of the push-pull hybrid data acquisition algorithm .

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CLC: > Industrial Technology > Automation technology,computer technology > Automation technology and equipment > Automation systems > Monitoring, alarm,fault diagnosis system
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