• Kavita Redishettywar Research Scholar, Department of Computer Science and Engineering, Matoshri Pratishthan Group of Institutions, Khupsarwadi, Nanded
  • Prof. Rafik Juber Thekiya Assistant Professor, Department of Computer Science and Engineering, Matoshri Pratishthan Group of Institutions, Khupsarwadi, Nanded


Cloud computing is a vigorous technology by which a user can get software, application, operating system and hardware as a service without actually possessing it and paying only according to the usage. Cloud Computing is a hot topic of research for the researchers these days. With the rapid growth of Interne technology cloud computing have become main source of computing for small as well big IT companies. In the cloud computing milieu the cloud data centers and the users of the cloud-computing are globally situated, therefore it is a big challenge for cloud data centers to efficiently handle the requests which are coming from millions of users and service them in an efficient manner. 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.


[1] S. Yakhchi, S. Ghafari, M. Yakhchi, M. Fazeli and A. Patooghy, "ICA-MMT: A Load Balancing Method in Cloud Computing Environment," IEEE, 2015.
[2] S. Kapoor and D. C. Dabas, "Cluster Based Load Balancing in Cloud Computing," IEEE, 2015.
[3] 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.
[4] R. Panwar and D. B. Mallick, "Load Balancing in Cloud Computing Using Dynamic Load Management Algorithm," IEEE, pp. 773-778, 2015.
[5] 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.
[6] L. Kang and X. Ting, "Application of Adaptive Load Balancing Algorithm Based on Minimum Traffic in Cloud Computing Architecture," IEEE, 2015.
[7] 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.
[8] H. H. Bhatt and H. A. Bheda, "Enhance Load Balancing using Flexible Load Sharing in Cloud Computing," IEEE, pp. 72-76, 2015.
[9] 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.
[10] 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.
[11] R. Kaur and P. Luthra, "LOAD BALANCING IN CLOUD COMPUTING," Int. J. of Network Security, , pp. 1-11, 2013.
[12] 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.
[13] 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.
[14] 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.
[15] 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.
[16] 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.
[17] 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.
[18] 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.
[19] 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.
[20] 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.
How to Cite
REDISHETTYWAR, Kavita; THEKIYA, Prof. Rafik Juber. AN ENHANCED TASK ALLOCATION STRATEGY IN CLOUD ENVIRONMENT. INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY, [S.l.], v. 16, n. 6, p. 6953-6961, aug. 2017. ISSN 2277-3061. Available at: <>. Date accessed: 20 oct. 2017. doi:

Most read articles by the same author(s)