Neural Load Prediction Technique for Power Optimization in Cloud Management System

被引：0

作者：

Nehru, Iniya E. ^{[1
]}

Venkatalakshmi, B. ^{[2
]}

Blakrishnan, Ranjith ^{[2
]}

Nithya, R. ^{[2
]}

机构：

[1] Natl Informat Ctr, Madras, Tamil Nadu, India

[2] Velammal Engn Coll, Dept Tifac Core Peruvas Comp Technol, Madras, Tamil Nadu, India

来源：

2013 IEEE CONFERENCE ON INFORMATION AND COMMUNICATION TECHNOLOGIES (ICT 2013) | 2013年

关键词：

Cloud Computing; Neural Network; Load balancing and Prediction; Power Optimization;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

Cloud computing is the current technology used for sharing and accessing resources via internet. It provides a scalable and cost effective environment. Large number of servers in the datacenters leads to huge consumption of power in the cloud computing scenario. Optimization of power consumption is a key challenge for effectively operating a datacenter. Power consumption can be regulated by using a proper load balancing technique. Load balancing is done so as to distribute the load fairly amidst the servers and also a scheduling technique is followed to selectively hibernate the servers to optimize the energy consumption. The load balancing is based on load prediction and server selection policy. Neural Network is used for load prediction, which predicts the future load based on the past historical data. The servers can be monitored and given ranking based on their reliability record and this information is used as a criterion while performing load balancing.

引用

页码：541 / 544

页数：4