Computer Science

Computer Science ›› 2019, Vol. 46 ›› Issue (9): 321-324.doi: 10.11896/j.issn.1002-137X.2019.09.049

• Interdiscipline & Frontier • Previous Articles     Next Articles

QoS Satisfaction Prediction of Cloud Service Based on Second Order Hidden Markov Model

JIA Zhi-chun1,2, LI Xiang1, YU Zhan-lin1, LU Yuan1, XING Xing1,2   

  1. (College of Information Science and Technology,Bohai University,Jinzhou,Liaoning 121013,China)1;
    (Institute of Automation,Bohai University,Jinzhou,Liaoning 121013,China)2
  • Received:2018-07-25 Online:2019-09-15 Published:2019-09-02

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Abstract: With the rapid development of cloud computing technology,QoS prediction of cloud service components has become an important research issue in cloud computing.Accurate prediction of the QoS value is of great difficulty in this research field.QoS is often used to measure the performance of different cloud service components.Based on the QoS values of different candidate components,it is easy to choose the best one.For the same cloud service component,the QoS values provided by different users are not necessarily the same.For different users,personalized component QoS values are needed so that accurate selection can be made.If the user’s QoS cannot be satisfied by a single cloud service component,the component composition should be considered.In this case,its QoS capability should to be predicted to meet the user’s needs.This paper presented a QoS satisfied prediction model of cloud service component.The model uses a second order hidden markov model to construct the QoS satisfaction predictive model.By considering the in- fluence of the previous two states on the current state,the proposed method can effectively improve the prediction accuracy.Finally,in the Matlab simulation experiment environment,the effectiveness of the proposed method is prove by the prototype system and QWS data set with 2507 real web services.

Key words: Cloud service, Second order hidden markov model, Service selection

CLC Number: 

  • TP391
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