2013•Unpublished venueRequires access

CLUSTER BASED BEE ALGORITHM FOR VIRTUAL MACHINE PLACEMENT IN CLOUD DATA CENTRE

Ajith B. Singh, M. Hemalatha

Open publisher page 23 citations

Abstract

The utilization of cloud data centres in combination with Virtualization technology has advantages of running more than one virtual machine in a single server. The data centres are a collection of many servers, allocation of VM to Host is known as VM placement. VM placement problem was examined in this paper with focus for maximum utilization of the resources and energy reduction. Switching off the idle server or in sleep mode can save energy consumption highly wasted in data centres. Technique for solving Virtual machine placement problem is implemented with the HoneyBee algorithm with hierarchical clustering in order to minimize energy consumption in servers. Cluster formation with the HoneyBee algorithm supports easy relocation of Virtual Machine migration and reduces the network latency. Further, simulation work with PlanetLab workload was experimented and revealed that the proposed HCT algorithm reduced energy consumption significantly while reducing the SLA and VM migration.

About this research paper

What this paper is about

The utilization of cloud data centres in combination with Virtualization technology has advantages of running more than one virtual machine in a single server. The data centres are a collection of many servers, allocation of VM to Host is known as VM placement. VM placement problem was examined in this paper with focus for maximum utilization of the resources and energy reduction. Switching off the idle server or in sleep mode can save energy consumption highly wasted in data centres. Technique for solving Virtual machine placement problem is implemented with the HoneyBee algorithm with hierarchical clustering in order to minimize energy consumption in servers. Cluster formation with the HoneyBee algorithm supports easy relocation of Virtual Machine migration and reduces the network latency. Further, simulation work with PlanetLab workload was experimented and revealed that the proposed HCT algorithm reduced energy consumption significantly while reducing the SLA and VM migration.

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OpenAlex reports 23 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

The utilization of cloud data centres in combination with Virtualization technology has advantages of running more than one virtual machine in a single server. The data centres are a collection of many servers, allocation of VM to Host is known as VM placement. VM placement problem was examined in this paper with focus for maximum utilization of the resources and energy reduction. Switching off the idle server or in sleep mode can save energy consumption highly wasted in data centres. Technique for solving Virtual machine placement problem is implemented with the HoneyBee algorithm with hierarchical clustering in order to minimize energy consumption in servers. Cluster formation with the HoneyBee algorithm supports easy relocation of Virtual Machine migration and reduces the network latency. Further, simulation work with PlanetLab workload was experimented and revealed that the proposed HCT algorithm reduced energy consumption significantly while reducing the SLA and VM migration.

Key concepts: PlanetLab, Virtual machine, Computer science, Server, Cloud computing, Energy consumption, Data center, Operating system

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