Evolutionary algorithm-based multi-objective task scheduling optimization model in cloud environments

Author:

Ramezani Fahimeh,Lu Jie,Taheri Javid,Hussain Farookh Khadeer

Publisher

Springer Science and Business Media LLC

Subject

Computer Networks and Communications,Hardware and Architecture,Software

Reference34 articles.

1. Alves, M.J.: Using MOPSO to solve multiobjective bilevel linear problems. Springer, Heidelberg (2012)

2. Buyya, R., Beloglazov, A., Abawajy, J.: Energy-efficient management of data center resources for cloud computing: A vision, architectural elements, and open challenges. arXiv preprint arXiv:1006.0308 (2010)

3. Calheiros, R.N., Ranjan, R., De Rose, C.A.F., Buyya, R.: Cloudsim: A novel framework for modeling and simulation of cloud computing infrastructures and services. Arxiv preprint arXiv:0903.2525 (2009)

4. Cirne, W., et al.: Labs of the world, unite!!! J. Grid Comput. 4(3), 225–246 (2006)

5. Deb, K., Pratap, A., Agarwal, S., Meyarivan, T.: A fast and elitist multiobjective genetic algorithm: NSGA-II. IEEE Trans. Evol. Comput. 6(2), 182–197 (2002)

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