Cluster Based Bee Algorithm for Virtual Machine Placement in Cloud Data Centre

نویسنده

  • M. HEMALATHA
چکیده

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.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Communication-Aware Traffic Stream Optimization for Virtual Machine Placement in Cloud Datacenters with VL2 Topology

By pervasiveness of cloud computing, a colossal amount of applications from gigantic organizations increasingly tend to rely on cloud services. These demands caused a great number of applications in form of couple of virtual machines (VMs) requests to be executed on data centers’ servers. Some of applications are as big as not possible to be processed upon a single VM. Also, there exists severa...

متن کامل

A Genetic Based Resource Management Algorithm Considering Energy Efficiency in Cloud Computing Systems

Cloud computing is a result of the continuing progress made in the areas of hardware, technologies related to the Internet, distributed computing and automated management. The Increasing demand has led to an increase in services resulting in the establishment of large-scale computing and data centers, in addition to high operating costs and huge amounts of electrical power consumption. Insuffic...

متن کامل

Basip a Virtual Machine Placement Technique to Reduce Energy Consumption in Cloud Data Centre

Infrastructure as a Service (IaaS) in cloud computing provides Infrastructure as a service for the demand of user from small instance to large instance in pay per use model. The services include like computer resource, networking and data storage. An API (Application Programming Interface) is used to access the infrastructure and a dashboard to control the server and to create and manage differ...

متن کامل

Analytical evaluation of an innovative decision-making algorithm for VM live migration

In order to achieve the virtual machines live migration, the two "pre-copy" and "post-copy" strategies are presented. Each of these strategies, depending on the operating conditions of the machine, may perform better than the other. In this article, a new algorithm is presented that automatically decides how the virtual machine live migration takes place. In this approach, the virtual machine m...

متن کامل

VM Consolidation by using Selection and Placement of VMs in Cloud Datacenters

The Cloud Computing model leverages virtualization of computing resources allowing customers to provision resources on-demand on a pay-as-you-go basis. During recent years, the power consumption of datacenters in cloud environment attracted researchers. Optimization of energy consumption can be performed by different methods including virtual machine (VM) consolidation. This technique can reduc...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2013