Main Reference PaperEnergy-Aware Scheduling Scheme Using Workload-Aware Consolidation Technique in Cloud Data Centres, December 2013.
  • The proposed approach introduces two algorithms called ESWCT and ELMWCT for managing cloud data centres to make full use of the resources. The ESWCT algorithm shows where to place the VM to get a better balance utilization of resource components among a physical server considering resource consumption. In order to use all the provided resources in cloud data centres, heterogeneous workloads should be consolidated to the minimum number of physical machines. Thus, idle servers can be switched to the sleep mode to reduce energy consumption. And we can dynamically migrate running VMs using ELMWCT from underused physical machines to others which are mostly fully used to reduce power consumption.

+ Description
  • The proposed approach introduces two algorithms called ESWCT and ELMWCT for managing cloud data centres to make full use of the resources. The ESWCT algorithm shows where to place the VM to get a better balance utilization of resource components among a physical server considering resource consumption. In order to use all the provided resources in cloud data centres, heterogeneous workloads should be consolidated to the minimum number of physical machines. Thus, idle servers can be switched to the sleep mode to reduce energy consumption. And we can dynamically migrate running VMs using ELMWCT from underused physical machines to others which are mostly fully used to reduce power consumption.

  • To reduce energy consumption based on VM placement on physical servers in cloud data centre.

  • To improve balanced utilization of workload and to minimize energy consumption using live VM migration.

  • To improve higher utilization of resources in cloud data centre.

+ Aim & Objectives
  • To reduce energy consumption based on VM placement on physical servers in cloud data centre.

  • To improve balanced utilization of workload and to minimize energy consumption using live VM migration.

  • To improve higher utilization of resources in cloud data centre.

  • Execution time consideration – Execution time of migrating VM consideration further reduces the energy consumption in cloud data center. The expected execution time of the migrating VM and other VMs are calculated. The PM which contains VM with an expected execution time as most similar as the migrating VM is identified and referred as the target PM. Matching of similar execution time of migrating VM and target PM minimizes the long execution time of physical server. Hence, it diminishes the energy consumption using idle server switched to sleep mode based on the matching of execution time.

+ Contribution
  • Execution time consideration – Execution time of migrating VM consideration further reduces the energy consumption in cloud data center. The expected execution time of the migrating VM and other VMs are calculated. The PM which contains VM with an expected execution time as most similar as the migrating VM is identified and referred as the target PM. Matching of similar execution time of migrating VM and target PM minimizes the long execution time of physical server. Hence, it diminishes the energy consumption using idle server switched to sleep mode based on the matching of execution time.

  • 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)

  • B.E / B.Tech / M.E / M.Tech

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

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