Abstract
The high popularity and growing demand of cloud computing has a strong effect on the cloud infrastructure providers to efficiently manage their cloud datacenters in order to fulfill provisioning of everything in the form of a service to end users and also to achieve efficient balancing between its less energy consumption for reduced environmental affects and maximize revue. This paper presents an energy efficient framework for green cloud datacenter which considers resource utilization and energy efficiency to support resource allocation decisions towards green computing. This work mainly relies on energy efficient provisioning of resources utilizing an application prediction and VM provisioning mechanism using genetic algorithm. Our approach has been validated by performing a set of experiments under dynamic cloud environment workload scenarios using Cloudsim toolkit. Compared to the benchmark (existing) algorithms, our method is able to significantly reduce the energy consumption cost without a priori knowledge of the future workloads.
Original language | English |
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Pages (from-to) | 3530-3537 |
Number of pages | 8 |
Journal | International Journal of Engineering and Technology(UAE) |
Volume | 7 |
Issue number | 4 |
DOIs | |
Publication status | Published - 01-01-2018 |
All Science Journal Classification (ASJC) codes
- Biotechnology
- Computer Science (miscellaneous)
- Environmental Engineering
- Chemical Engineering(all)
- Engineering(all)
- Hardware and Architecture