Main Reference PaperDynamic resource demand prediction and allocation in multi‐tenant service clouds, Concurrency and Computation: Practice and Experience (2016) [Java/Cloudsim].
  • The prediction framework predicts the future resources demand based on past behavior of resource requirements of service tenants. The prediction framework exploits a Logistic regression classification model to classify the service tenants in order to understand whether their resource requirements are increasing or decreasing.

+ Description
  • The prediction framework predicts the future resources demand based on past behavior of resource requirements of service tenants. The prediction framework exploits a Logistic regression classification model to classify the service tenants in order to understand whether their resource requirements are increasing or decreasing.

  • To allow the dynamic scaling of resources, it requires a highly accurate demand prediction and resource allocation methodology.

  • The dynamic Resource Allocation allocates the service tenants to correct VM and the VM allocates to suitable physical host.

  • To reduce the VM downtime.

+ Aim & Objectives
  • To allow the dynamic scaling of resources, it requires a highly accurate demand prediction and resource allocation methodology.

  • The dynamic Resource Allocation allocates the service tenants to correct VM and the VM allocates to suitable physical host.

  • To reduce the VM downtime.

  • Each time VMs are placed into physical host machine using best-fit decreasing heuristic algorithm.

+ Contribution
  • Each time VMs are placed into physical host machine using best-fit decreasing heuristic algorithm.

  • Java JDK 1.8, MySQL 5.5.40.

  • Netbeans 8.0.1, & J2SE, and Cloudsim 3.0.3

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

  • Netbeans 8.0.1, & J2SE, and 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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