By Topic

A Cloud Computing Resource Scheduling Policy Based on Genetic Algorithm with Multiple Fitness

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Shi Chen ; Sch. of Comput. Sci. & Technol., Fudan Univ., Shanghai, China ; Jie Wu ; Zhihui Lu

Under the cloud computing environment of IaaS(Infrastructure as a Service), due to the expansion of system scale and virtual machines' migrations, etc, it is easy to cause some problems like fragmentation of physical resources, low utilization of resources. The consequences lead to high energy consumption within an Internet Data center. In this paper, we propose a pre-migration strategy based on three load dimensions: CPU utilization, network throughput, disk I/O rate, which are considered complementary in the algorithm. In order to get an approximately optimal solution, we adopt the hybrid genetic algorithm combined with knapsack problem with multiple fitness and experiments are conducted to verify the effectiveness of the algorithm. The result of the experiments shows that the algorithm can effectively achieve the goal of raising resources' utilization and lowering energy consumption under cloud computing environment.

Published in:

Computer and Information Technology (CIT), 2012 IEEE 12th International Conference on

Date of Conference:

27-29 Oct. 2012