Open Access

Pareto Based Virtual Machine Selection with Load Balancing in Cloud Data Centre


Cite

1. Buyya, R. K., et al. Cloud Computing and Emerging IT Platforms: Vision, Hype, and Reality for Delivering Computing as the 5th Utility. – Future Generation Computer Systems, Vol. 25, 2009, No 6, pp. 599-616.10.1016/j.future.2008.12.001Search in Google Scholar

2. Li, W., J. Tordsson, E. Elmroth. Modelling for Dynamic Cloud Scheduling via Migration of Virtual Machines. – In: Proc. of 3rd IEEE Int. Conf. Cloud Comput. Technol. Sci. CloudCom’2011, 2011, pp. 163-171.10.1109/CloudCom.2011.31Search in Google Scholar

3. Davis, L. J., L. J. Davis. Selection of Load Balancing Parameters. – Vol. 9655, 2015, No October.Search in Google Scholar

4. Ullman, J. D. NP-Complete Scheduling Problems. – Journal of Computer and System Sciences, Vol. 10, 1975, No 3, pp. 384-393.10.1016/S0022-0000(75)80008-0Search in Google Scholar

5. Srinivas, N., K. Deb. Multiobjective Optimization Using No Dominated Sorting in Genetic Algorithms. – Evol. Comput., Vol. 2, 1995, No 3, pp. 221-248.10.1162/evco.1994.2.3.221Search in Google Scholar

6. Yair, C. Pareto Optimality in Multiobjective Problems. – Applied Mathematics and Optimization, Vol. 4, 1977, No 1, pp. 41-59.10.1007/BF01442131Search in Google Scholar

7. Liu, Q., et al. An Adaptive Approach to Better Load Balancing in a Consumer-Centric Cloud Environment. – IEEE Transactions on Consumer Electronics, Vol. 62, 2016, No 3, pp. 243-250.10.1109/TCE.2016.7613190Search in Google Scholar

8. Shaw, S. B. Balancing Load of Cloud Data Centre Using Efficient Task Scheduling Algorithm. – International Journal of Computer Applications, Vol. 159, 2017, No 5, pp. 1-5.10.5120/ijca2017910945Search in Google Scholar

9. Ayyapazham, R., K. Velautham. Proficient Decision Making on Virtual Machine Creation in IaaS Cloud Environment. – Vol. 14, 2017, No 3, pp. 314-323.Search in Google Scholar

10. Rajeev, K., T. Prashar. A Bio-Inspired Hybrid Algorithm for Effective Load Balancing in Cloud Computing. – International Journal of Cloud Computing, Vol. 5, 2016, No 3, pp. 218-246.10.1504/IJCC.2016.10000909Search in Google Scholar

11. Devi, D. C., V. R. Uthariaraj. Load Balancing in Cloud Computing Environment Using Improved Weighted Round Robin Algorithm for Nonpreemptive Dependent Tasks. – The Scientific World Journal, Vol. 2016, 2016.10.1155/2016/3896065475621426955656Search in Google Scholar

12. Feng, Y., et al. A Novel Cloud Load Balancing Mechanism in Premise of Ensuring QoS. – Intelligent Automation & Soft Computing, Vol. 19, 2013, No 2, pp. 151-163.10.1080/10798587.2013.786968Search in Google Scholar

13. Bhatt, H., H. A. Bheda. Enhance Load Balancing Using Flexible Load Sharing in Cloud Computing. – 2015, No September, pp. 4-5.10.1109/NGCT.2015.7375085Search in Google Scholar

14. Liu, C. A Load Balancing Aware Virtual Machine Live Migration Algorithm. – In: Proc. of International Conference on Sensors, Measurement and Intelligent Materials, 2016.10.2991/icsmim-15.2016.69Search in Google Scholar

15. Shikha, G., R. K. Dwivedi, H. Chauhan. Efficient Utilization of Virtual Machines in Cloud Computing Using Synchronized Throttled Load Balancing. – Proc. of 1st International Conference on Next Generation Computing Technologies (NGCT’15), IEEE, 2015.Search in Google Scholar

16. Pham, N. M. N., H. H. C. Nguyen. Energy Efficient Resource Allocation for Virtual Services Based on Heterogeneous Shared Hosting Platforms in Cloud Computing. – Cybernetic and Information Technologies, Vol. 17, 2017, No 3, pp. 47-58.10.1515/cait-2017-0029Search in Google Scholar

17. Atyaf, D., K. I. Arif. An Efficient Load Balancing Scheme for Cloud Computing. – Indian Journal of Science and Technology, Vol. 10, 2017, No 11.10.17485/ijst/2017/v10i11/110107Search in Google Scholar

18. Deb, K., S. Agrawal, A. Pratap, T. Meyarivan. A Fast Elitist Non-Dominated Sorting Genetic Algorithm for Multi-Objective Optimization: NSGA-II. – Parallel Probl. Solving from Nat. PPSN VI, 2000, pp. 849-858.10.1007/3-540-45356-3_83Search in Google Scholar

19. Ruiz, R., C. Maroto, J. Alcaraz. Two New Robust Genetic Algorithms for the Flow Shop Scheduling Problem. – Omega, Vol. 34, 2006, No 5, pp. 461-476.10.1016/j.omega.2004.12.006Search in Google Scholar

20. Mitsuo, G., F. Altiparmak, L. Lin. A Genetic Algorithm for Two-Stage Transportation Problem Using Priority-Based Encoding. – OR Spectrum, Vol. 28, 2006, No 3, pp. 337-354.10.1007/s00291-005-0029-9Search in Google Scholar

21. Feitelson, D. G. Parallel Workload Archive, 2007. http://www.cs.huji.ac.il/labs/parallel/workloadSearch in Google Scholar

22. Kalyanmoy, D., et al. A Fast Elitist Non-Dominated Sorting Genetic Algorithm for Multi-Objective Optimization: NSGA-II. – In: Proc. of International Conference on Parallel Problem Solving From Nature. Springer, Berlin, Heidelberg, 2000.Search in Google Scholar

eISSN:
1314-4081
Language:
English
Publication timeframe:
4 times per year
Journal Subjects:
Computer Sciences, Information Technology