Volume- 3
Issue- 2
Year- 2015
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Anindita Kundu , .
Cloud Computing is the distributed computing on internet or delivery of computing services over the internet. Cloud computing involves deploying groups of remote servers and software networks that allow centralized data storage and online access to computer services or resources. Cloud Computing allows the customers to apply the application without set up and access their own files on any device with internet. The cloud service providers have developed the cloud enough to provide services to any number of users. Cloud is a set of virtualized resources that can be produced as demand of the user. In cloud computing basically there are three components: one is the host that represents a physical computing, second is the datacenter that is a collection of server for managing Virtual Machines during their life cycles. Here application is placed, which is accessed by internet. The last is the distributed servers that are in different places but acts as near to the next one. One important issue is the handling of requests from the various machines so that all the tasks can be completed in minimum waiting time. This paper presents and examine a new scheduling algorithm with the use of fuzzy control system for scheduling virtual machines between datacenters. The experimental results show the effectiveness of our algorithm by comparing it with the three scheduling techniques First Come First Serve (FCFS), Round Robin (RR) and Honeybee Foraging (HF) algorithm.
[1] R. Buyya, C. S. Yeo, S. Venugopal, J. Broberg and I. Brandic, Cloud computing and emerging IT platforms: vision, hype, and reality for delivering computing as the 5th utility, Future generation system, 2009.
[2] Amin Mehranzadeh, Seyyed Mohsen Hashemi International Journal of Applied Information Systems (IJAIS): A Novel-Scheduling Algorithm for Cloud Computing based on Fuzzy Logic, Volume 5– No.7, May 2013.
[3] Suriya Begum, Dr. Prashanth C.S.R, IJCSI International Journal of Computer Science Issues : Review of Load Balancing in Cloud Computing, Vol. 10, Issue 1, No 2, January 2013.
[4] N. S. Raghava and Deepti Singh, OPEN JOURNAL OF MOBILE COMPUTING AND CLOUD COMPUTING: Comparative Study on Load Balancing Techniques in Cloud Computing, Volume 1, Number 1, August 2014.
[5] Sandeep Sharma, Sarabjit Singh, and Meenakshi Sharma, “Performance Analysis of Load Balancing Algorithms” World Academy of Science, Engineering and Technology 14 2008.
[6] A.Y.Zomaya, and Y.The, "Observations on using genetic algorithms for dynamic load-balancing", IEEE Transaction on parallel and Distributed Systems, vol. 12, no. 9, 899-911, 2001.
[7] Asitha Micheal, Jalpa Mehta “Load Balancing Techniques in Cloud Computing”, International Journal on Recent and Innovation Trends in Computing and Communication, Volume: 2 Issue: 10.
[8] D.Driankov, H.Hellendoom and M.Reinfrank, An introduction to fuzzy control, Springer-Verlag, Berlin, New York, 1993.
[9] Book on “Fuzzy Logic- With Engineering Application” by Timothy J. Rose, Wiley Edition.
Computer Science Department, Sadabai Raisoni Women’s College (SRWC), Nagpur, INDIA, 9970835545
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