An Energy Efficient and SLA Compliant Approach for Resource Allocation and Consolidation in Cloud Computing Environments

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An Energy Efficient and SLA Compliant Approach for Resource Allocation and Consolidation in Cloud Computing Environments

An Energy Efficient and SLA Compliant Approach for Resource Allocation and Consolidation in Cloud Computing Environments

Abstract

Cloud computing is a promising paradigm that allows a “computing-as – a-service” model in which a dynamic pool of virtualized computational resources (e.g. CPU) can be leased and released on demand. An Energy Efficient and SLA Compliant Approach for Resource Allocation and Consolidation in Cloud Computing Environments With the increased demand for infrastructure for cloud computing and the explosion in data center sizes, energy efficiency becomes a major issue to consider.  Green cloud computing is an area that focuses on the design of energy-efficient data centers to achieve cost savings and minimize negative impacts on the environment.

One of the main An Energy Efficient and SLA Compliant Approach for Resource Allocation and Consolidation in Cloud Computing Environments used to reduce energy consumption is maximizing the use of a number of physical machines (PMs) and turning off or suspending unused servers.

An Energy Efficient and SLA Compliant Approach for Resource Allocation and Consolidation in Cloud Computing Environments
 

System Configuration

H/W System Configuration

Speed                   : 1.1 GHz
 
RAM                      : 256 MB(min)
 
Hard Disk              : 20 GB
 
Floppy Drive          : 1.44 MB
 
Key Board             : Standard Windows Keyboard
 
Mouse                  : Two or Three Button Mouse
 
Monitor                : SVGA
 
S/W System Configuration
 
 
Platform                     :  cloud computing
 
Operating system       : Windows Xp,7,
 
Server                       : WAMP/Apache
 
Working on                : Browser Like Firefox, IE

Conclusion

With the growing demands for cloud computing services and infrastructures, there is a need for new solutions that can support QoS and SLA requirements while ensuring energy efficiency in data centers. This work focused on the placement and consolidation algorithms for energy-aware and QoS-aware VMs. Our proposed approach aims at achieving a balance between energy consumption and performance of the system using two complementary algorithms: a placement algorithm for multi-objective ACO VMs and a consolidation algorithm for multi-objective ACO VMs.