<abstract xmlns="http://www.w3.org/1999/xhtml"><p>The goal of data centers in the cloud computing environment is to provision the workloads and the computing resources as demanded by the users without the intervention of the providers. To achieve this, virtualization based server consolidation acts as a vital part in virtual machine placement process. Consolidating the Virtual Machines (VMs) on the Physical Machines (PMs) cuts down the unused physical servers, decreasing the energy consumption, while keeping the constraints for CPU and memory utilization. This technique also reduces the resource wastage and optimizes the available resources efficiently. Ant Colony Optimization (ACO) that is a well-known multi objective heuristic algorithm and Grey Wolf Algorithm (GWO) has been used to consolidate the servers used in the virtual machine placement problem. The proposed Fuzzy HAGA algorithm outperforms the other algorithms MMAS, ACS, FFD and Fuzzy ACS compared against it as the number of processors and memory utilization are lesser than these algorithms.</p></abstract>

The goal of data centers in the cloud computing environment is to provision the workloads and the computing resources as demanded by the users without the intervention of the providers. To achieve this, virtualization based server consolidation acts as a vital part in virtual machine placement process. Consolidating the Virtual Machines (VMs) on the Physical Machines (PMs) cuts down the unused physical servers, decreasing the energy consumption, while keeping the constraints for CPU and memory utilization. This technique also reduces the resource wastage and optimizes the available resources efficiently. Ant Colony Optimization (ACO) that is a well-known multi objective heuristic algorithm and Grey Wolf Algorithm (GWO) has been used to consolidate the servers used in the virtual machine placement problem. The proposed Fuzzy HAGA algorithm outperforms the other algorithms MMAS, ACS, FFD and Fuzzy ACS compared against it as the number of processors and memory utilization are lesser than these algorithms.

A Hybrid Technique for Server Consolidation in Cloud Computing Environment

Cybernetics and Information Technologies

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

{"article-title":"A Hybrid Technique for Server Consolidation in Cloud Computing Environment"}

The goal of data centers in the cloud computing environment is to provision the workloads and the computing resources as demanded by the users without the...

A Hybrid Technique for Server Consolidation in Cloud Computing Environment

Data publikacji: 27 mar 2020

Zakres stron: 36 - 52

Otrzymano: 31 paź 2018

Przyjęty: 27 gru 2019

DOI: https://doi.org/10.2478/cait-2020-0003

Słowa kluczowe
Virtual Machine (VM) placement, VM, power consumption, resource wastage, Ant Colony Optimization (ACO), Grey Wolf Optimisation (GWO) Algorithm, HAGA Algorithm

© 2020 C. Vijaya et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

A Hybrid Technique for Server Consolidation in Cloud Computing Environment

Data publikacji: 27 mar 2020

Zakres stron: 36 - 52

Otrzymano: 31 paź 2018

Przyjęty: 27 gru 2019

DOI: https://doi.org/10.2478/cait-2020-0003

Słowa kluczoweVirtual Machine (VM) placement, VM, power consumption, resource wastage, Ant Colony Optimization (ACO), Grey Wolf Optimisation (GWO) Algorithm, HAGA Algorithm

© 2020 C. Vijaya et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Słowa kluczowe
Virtual Machine (VM) placement, VM, power consumption, resource wastage, Ant Colony Optimization (ACO), Grey Wolf Optimisation (GWO) Algorithm, HAGA Algorithm