Main Reference PaperQoS Ranking Prediction for Cloud Services, IEEE Transactions on Parallel and Distributed Systems, June 2013
  • This paper proposes a QoS ranking prediction framework for cloud services by taking advantage of the past service usage experiences of other consumers. The proposed framework requires no additional invocations of cloud services when making QoS ranking prediction. Two personalized QoS ranking prediction approaches are suggested to predict the QoS rankings directly.

+ Description
  • This paper proposes a QoS ranking prediction framework for cloud services by taking advantage of the past service usage experiences of other consumers. The proposed framework requires no additional invocations of cloud services when making QoS ranking prediction. Two personalized QoS ranking prediction approaches are suggested to predict the QoS rankings directly.

  • To reduce the expense by predicting the QoS of the cloud service before using it in real time

+ Aim & Objectives
  • To reduce the expense by predicting the QoS of the cloud service before using it in real time

  • Collaborative Filtering Approach is used for similarity computation that improves the accuracy of prediction and reduces the computation cost

+ Contribution
  • Collaborative Filtering Approach is used for similarity computation that improves the accuracy of prediction and reduces the computation cost

  • Java JDK 1.8, MySQL 5.5.40

  • Netbeans 8.0.1, J2SE, (Cloudsim 3.0.3)

+ Software Tools & Technologies
  • Java JDK 1.8, MySQL 5.5.40

  • Netbeans 8.0.1, J2SE, (Cloudsim 3.0.3)

  • M.E / M.Tech / MS / Ph.D.- Customized according to the client requirements.

+ Project Recommended For
  • M.E / M.Tech / MS / Ph.D.- Customized according to the client requirements.

  • No Readymade Projects-Depending on the complexity of the project and requirements.

+ Order To Delivery
  • No Readymade Projects-Depending on the complexity of the project and requirements.

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