The IRMA Community
Newsletters
Research IRM
Click a keyword to search titles using our InfoSci-OnDemand powered search:
|
Energy and SLA Efficient Virtual Machine Placement in Cloud Environment Using Non-Dominated Sorting Genetic Algorithm
Abstract
To increase the availability of the resources and simultaneously to reduce the energy consumption of data centers by providing a good level of the service are one of the major challenges in the cloud environment. With the increasing data centers and their size around the world, the focus of the current research is to save the consumption of energy inside data centers. Thus, this article presents an energy-efficient VM placement algorithm for the mapping of virtual machines over physical machines. The idea of the mapping of virtual machines over physical machines is to lessen the count of physical machines used inside the data center. In the proposed algorithm, the problem of VM placement is formulated using a non-dominated sorting genetic algorithm based multi-objective optimization. The objectives are: optimization of the energy consumption, reduction of the level of SLA violation and the minimization of the migration count.
Related Content
Shailendra Aote, Mukesh M. Raghuwanshi.
© 2021.
34 pages.
|
Anjana Mishra, Bighnaraj Naik, Suresh Kumar Srichandan.
© 2021.
15 pages.
|
Thendral Puyalnithi, Madhuviswanatham Vankadara.
© 2021.
15 pages.
|
Geng Zhang, Xiansheng Gong, Xirui Chen.
© 2021.
13 pages.
|
Jhuma Ray, Siddhartha Bhattacharyya, N. Bhupendro Singh.
© 2021.
19 pages.
|
Pijush Samui, Viswanathan R., Jagan J., Pradeep U. Kurup.
© 2021.
18 pages.
|
Ravinesh C. Deo, Sujan Ghimire, Nathan J. Downs, Nawin Raj.
© 2021.
32 pages.
|
|
|