Abstract

Although cloud computing is now becoming more advanced and matured as many companies have released their own computing platforms to provide services to public, but the research on cloud computing is still in its infancy. Apart from many other challenges of cloud computing, efficient management of energy is one of the most challenging research issues. In this paper we review the existing algorithm of dynamic resource provisioning and allocation algorithms and holistically work to boost data center energy efficiency and performance. This particular paper purposes a) heterogeneous workload and its implication on data centers energy efficiency b) solving the problem of VM resource scheduling to cloud applications

Highlights

  • Cloud computing has been widely adopted by the industry, but the research on cloud computing is still at an infancy stage

  • Load balancing of the entire system can be dynamically handled by using virtualization technology through which it becomes possible to remap virtual machine and physical resources according to the change in load

  • This paper is based on cloud computing technology which has a very vast potential and is still unexplored

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Summary

INTRODUCTION

Cloud computing has been widely adopted by the industry, but the research on cloud computing is still at an infancy stage. Aim of the thesis is to consolidate the load balancing in an efficient way so that the resource utilization can be maximized and the energy consumption of the data center could be minimized that can further result in reducing global warming and assist in achieving Green Computing. The other main problem in cloud computing is how efficiently we manage the resources[6] By doing this some machine goes to idle state and we can turn off these machines to save energy. Modern resource-intensive scientific applications and enterprise create growing demand for high performance computing infrastructures This has led to the construction of large-scale computing data centers consuming enormous amounts of electrical power. It includes data produced from cell phone bills or from online transactions

Database Workloads
RELATED WORK
Coldspot
Green computing
Findings
CONCLUSION
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