Prediction Based Energy Efficient Technique for Enterprise Cloud Datacenters
Cloud Computing, Energy efficiency, Prediction, Sleep states
Cloud Data centers use huge amount of electrical energy. And electrical energy is a very useful resource for the development of the country. With the need for dynamic computing resources and pay-per-use payment for the computing resources cloud computing is gaining much attention in recent times. Many cloud architectures are available in the market. But most of them do not take care about the efficient use of energy resources. The type of task scheduling greatly affects the energy consumption of a cloud data center. According to estimation Google data centers uses electrical energy that is equivalent to the energy requirement of a small size city. This work is all about to propose a dynamic idle interval prediction scheme that can estimate future CPU idle interval lengths and thereby choose the most cost-effective sleep state to minimize power consumption at runtime. Experiments show that our proposed approach can significantly outperform other existing schemes.
"Prediction Based Energy Efficient Technique for Enterprise Cloud Datacenters", IJSDR - International Journal of Scientific Development and Research (www.IJSDR.org), ISSN:2455-2631, Vol.1, Issue 3, page no.171 - 173, March-2016, Available :https://ijsdr.org/papers/IJSDR1603033.pdf
Volume 1
Issue 3,
March-2016
Pages : 171 - 173
Paper Reg. ID: IJSDR_160082
Published Paper Id: IJSDR1603033
Downloads: 000347032
Research Area: Engineering
Country: Hosur, Tamilnadu, India
ISSN: 2455-2631 | IMPACT FACTOR: 9.15 Calculated By Google Scholar | ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 9.15 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
Publisher: IJSDR(IJ Publication) Janvi Wave
