The week's pick
Reseach Article
Optimal Scheduling and Load Balancing in Cloud using Enhanced Genetic Algorithm
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 125 - Number 11 |
| Year of Publication: 2015 |
| Authors: Kiranveer Kaur, Amritpal Kaur |
10.5120/ijca2015906084
|
Kiranveer Kaur, Amritpal Kaur . Optimal Scheduling and Load Balancing in Cloud using Enhanced Genetic Algorithm. International Journal of Computer Applications. 125, 11 ( September 2015), 1-6. DOI=10.5120/ijca2015906084
Abstract
The cloud computing is the enlargement of distributed computing, equivalent computing and gridiron computing, or defined as the commercial achievement of these computer science concepts. One of the elementary issues in these circumstances is interrelated to task scheduling and Load Balancing. Cloud task arrangement is an NP-hard optimization dilemma, and numerous meta-heuristic algorithms have been anticipated to crack it. A superior task scheduler should acclimatize its arrangement stratagem to the varying situation and the types of tasks. This manuscript proposes a cloud task arrangement course of action based on Load Balancing Enhanced Genetic (EGA) algorithm. The major involvement of our exertion is to balance the whole system load although trying to minimizing the Makespan of a prearranged tasks set. The innovative scheduling strategy was simulated using the Net Beans toolkit package. Experiments results showed the proposed Enhanced Genetic (EGA) algorithm and Compare the EGA, ACO.
References
- Kiranveer kaur and Amritpal kaur, “Survey of Load Balancing Algorithm in Cloud”, International Journal of Engineering Research and Technology (IJERT), ISSN: 2278-0181, Vol. 4, Issue 3, March 2015.
- Amandeep kaur sidhu and Supriya kinger, “Analysis of Load Balancing Techniques in Cloud Computing”, International Journal of Computer and Technology, ISSN: 2277-3061, Vol. 4, No. 2, March-April 2013.
- Shilpa V Pius and Shilpa T S, “Survey on Load Balancing in Cloud Computing”, International Conference on Computing, Communication and Energy Systems (ICCCES), 2014.
- Tingting Wang, Zhaobin Liu, Yi Chen, Yujie Xu, “Load Balancing Task Scheduling based on Genetic Algoritm in Cloud Computing”, IEEE 12th International Conference on Dependable, Autonomic and Secure Computing, 2014.
- Saeed Javanmardi, MohammadShojafar, Danilo Amendola, Nicola Cordeschi, “Hybrid Job Scheduling Algorithm for Cloud Computing Environment”, adfa, 2014.
- Tarun Goyal, Aakankaha Agrawal, “Host Scheduling Algorithm using Genetic Algorithm in Cloud Computing Environment”, International Journal of Research in Engineering and Technology (IJERT), Vol. 1, June 2013.
- Lucio Agostinho, Guilherme Feliciano, Leonardo Olivi, Eleri Cardozo, “A Bio-Inspired Approach to Provisioning of Virtual Resources in Federated Clouds”, IEEE Ninth International Conference on Dependable, Autonomic and Secure Computing, 2011,pp.548-604.
- Andrew J. Younge, Gregor von Laszewski, Lizhe Wang, Sonia Lopez-Alarcon, Warren Carithers, “Efficient Resource Management for Cloud Computing Environments”, IEEE, 2010.
- Rajkumar Buyya, Rajiv Ranjan, Rodrigo N.Calheriros, “Modeling and Simulation of Scalable Cloud Computing Environment and the CloudSim Toolkit: Challanges and Opportunities”, International Conference on High Performance Computing and Simulation, HPCS 2009.
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