A NOVEL APPROACH OF OPTIMIZING PERFORMANCE USING K-MEANS CLUSTERING IN CLOUD COMPUTING
Cloud computing is distributed computing, storing, sharing and accessing data over the Internet. It provides a pool of shared resources to the users available on the basis of pay as you go service that means users pay only for those services which are used by him according to their access times. Load balancing ensures that no single node will be overloaded and used to distribute workload among multiple nodes. It helps to improve system performance and proper utilization of resources. We propose an improved load balancing algorithm for job scheduling in the cloud environment using K-Means clustering of cloudlets and virtual machines in the cloud environment. All the cloudlets given by the user are divided into 3 clusters depending upon client’s priority, cost and instruction length of the cloudlet. The virtual machines inside the datacenter hosts are also grouped into multiple clusters depending upon virtual machine capacity in terms of processor, memory, and bandwidth. Sorting is applied at both the ends to reduce the latency. Multiple number of experiments have been conducted by taking different configurations of cloudlets and virtual machine. Various parameters like waiting time, execution time, turnaround time and the usage cost have been computed inside the cloudsim environment to demonstrate the results. Compared with the other job scheduling algorithms, the improved load balancing algorithm can outperform them according to the experimental results.
 S. Kapoor and D. C. Dabas, "Cluster Based Load Balancing in Cloud Computing," IEEE, 2015.
 S. Garg, R. Kumar and H. Chauhan, "Efﬁcient Utilization of Virtual Machines in Cloud Computing using Synchronized Throttled Load Balancing," 1st International Conference on Next Generation Computing Technologies (NGCT-2015), pp. 77-80, 2015.
 R. Panwar and D. B. Mallick, "Load Balancing in Cloud Computing Using Dynamic Load Management Algorithm," IEEE, pp. 773-778, 2015.
 M. Belkhouraf, A. Kartit, H. Ouahmane, H. K. Idrissi,, Z. Kartit and M. . E. Marraki, "A secured load balancing architecture for cloud computing based on multiple clusters," IEEE, 2015.
 L. Kang and X. Ting, "Application of Adaptive Load Balancing Algorithm Based on Minimum Traffic in Cloud Computing Architecture," IEEE, 2015.
 N. K. Chien, N. H. Son and H. D. Loc, "Load Balancing Algorithm Based on Estimating Finish Time of Services in Cloud Computing," ICACT, pp. 228-233, 2016.
 H. H. Bhatt and H. A. Bheda, "Enhance Load Balancing using Flexible Load Sharing in Cloud Computing," IEEE, pp. 72-76, 2015.
 S. S. MOHARANA, R. D. RAMESH and D. POWAR, "ANALYSIS OF LOAD BALANCERS IN CLOUD COMPUTING," International Journal of Computer Sciencand Engineering (IJCSE) , pp. 102-107, 2013.
 M. P. V. Patel, H. D. Patel and . P. J. Patel, "A Survey On Load Balancing In Cloud Computing," International Journal of Engineering Research & Technology (IJERT), pp. 1-5, 2012.
 R. Kaur and P. Luthra, "LOAD BALANCING IN CLOUD COMPUTING," Int. J. of Network Security, , pp. 1-11, 2013.
 Kumar Nishant, , P. Sharma, V. Krishna, Nitin and R. Rastogi, "Load Balancing of Nodes in Cloud Using Ant Colony Optimization," IEEE, pp. 3-9, 2012.
 Y. Xu, L. Wu, L. Guo,, Z. Chen, L. Yang and Z. Shi, "An Intelligent Load Balancing Algorithm Towards Efﬁcient Cloud Computing," AI for Data Center Management and Cloud Computing: Papers from the 2011 AAAI Workshop (WS-11-08), pp. 27-32, 2011.
 A. K. Sidhu and S. Kinger, "Analysis of Load Balancing Techniques in Cloud Computing," International Journal of Computers & Technology Volume 4 No. 2, March-April, 2013, ISSN 2277-3061 , pp. 737-741, 2013.
 O. M. Elzeki , M. Z. Reshad and M. A. Elsoud , "Improved Max-Min Algorithm in Cloud Computing," International Journal of Computer Applications (0975 – 8887), pp. 22-27, 2012.
 B. Kruekaew and W. Kimpan, "Virtual Machine Scheduling Management on Cloud Computing Using Artificial Bee Colony," Proceedings of the International MultiConference of Engineers and Computer Scientists 2014 Vol I,IMECS 2014, 2014.
 R.-S. Chang, J.-S. Chang and P.-S. Lin, "An ant algorithm for balanced job scheduling in grids," Future Generation Computer Systems 25 (2009) 20–27, pp. 21-27, 2009.
 Z. Chaczko, V. Mahadevan, S. Aslanzadeh and C. Mcdermid, "Availability and Load Balancing in Cloud Computing," International Conference on Computer and Software Modeling IPCSIT vol.14 (2011) © (2011) IACSIT Press, Singapore, pp. 134-140, 2011.
 R. K. S, S. V and V. M, "Enhanced Load Balancing Approach to Avoid Deadlocks in Cloud," Special Issue of International Journal of Computer Applications (0975 – 8887) on Advanced Computing and Communication Technologies for HPC Applications - ACCTHPCA, June 2012, pp. 31-35, 2012.
 Kumar Nishant, , P. Sharma, V. Krishna, N. and R. Rastogi, "Load Balancing of Nodes in Cloud Using Ant Colony Optimization," IEEE, pp. 3-9, 2012.
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