Main Reference PaperSLA-aware Provisioning and Scheduling of Cloud Resources for Big Data Analytics, IEEE, 2014.
  • The proposed SLA and cost-aware resource provisioning a task scheduling approach is tailored for Big Data applications in the Cloud. An admission control and cloud resource scheduling and provisioning mechanism which not only maximize the resource utilization but also ensures the SLO objectives (deadline and budget). Branch and Bound for a Pruned Tree algorithm is used to provision resources and schedule tasks from given users with SLA constraints (budget and deadline). Each data center within a cloud provider have an admission controller which makes the decision to accept or reject a new application to avoid overloading of resources and satisfy the SLA constraints.

+ Description
  • The proposed SLA and cost-aware resource provisioning a task scheduling approach is tailored for Big Data applications in the Cloud. An admission control and cloud resource scheduling and provisioning mechanism which not only maximize the resource utilization but also ensures the SLO objectives (deadline and budget). Branch and Bound for a Pruned Tree algorithm is used to provision resources and schedule tasks from given users with SLA constraints (budget and deadline). Each data center within a cloud provider have an admission controller which makes the decision to accept or reject a new application to avoid overloading of resources and satisfy the SLA constraints.

  • To avoid overloading of resources in data centers.

  • To build a model for SLA-based resource provisioning

  • To build a model for tasks scheduling for Big Data Processing in cloud environments.

+ Aim & Objectives
  • To avoid overloading of resources in data centers.

  • To build a model for SLA-based resource provisioning

  • To build a model for tasks scheduling for Big Data Processing in cloud environments.

  • Support Vector Machine – Support vector machine (SVM) , a machine learning method is used as an admission control policy at entry point. Each data center within a cloud provider have an admission controller which makes the decision to accept or reject a new application to avoid overloading of resources and satisfy the SLA constraints, by using SVM machine learning algorithm which helps inresource monitoring and prediction and decides upon which datacenter to select which satisfy the SLA constraints and increase the performance.

+ Contribution
  • Support Vector Machine – Support vector machine (SVM) , a machine learning method is used as an admission control policy at entry point. Each data center within a cloud provider have an admission controller which makes the decision to accept or reject a new application to avoid overloading of resources and satisfy the SLA constraints, by using SVM machine learning algorithm which helps inresource monitoring and prediction and decides upon which datacenter to select which satisfy the SLA constraints and increase the performance.

  • Java JDK 1.8, MySQL

  • Netbeans 8.0.1, J2SE, (Cloudsim).

+ Software Tools & Technologies
  • Java JDK 1.8, MySQL

  • Netbeans 8.0.1, J2SE, (Cloudsim).

  • B.E / B.Tech / M.E / M.Tech

+ Project Recommended For
  • B.E / B.Tech / M.E / M.Tech

  • 10 – 15 Days

+ Order To Delivery
  • 10 – 15 Days

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