ENHANCING JOB ALLOCATION USING NBST IN CLOUD ENVIRONMENT: A REVIEW
DOI:
https://doi.org/10.24297/ijct.v16i3.6182Keywords:
Cloud computing, Load balancing, Virtual machine, Host, Datacenter, Datacenter BrokerAbstract
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 is a critical aspect that ensures that all the resources and entities are well balanced such that no resource or entity neither is under loaded nor overloaded. The load balancing algorithms can be static or dynamic. Load balancing in this environment means equal distribution of workload across all the nodes. Load balancing provides a way of achieving the proper utilization of resources and better user satisfaction. Hence, use of an appropriate load balancing algorithm is necessary for selecting the virtual machines or servers. This paper focuses on the load balancing algorithm which distributes the incoming jobs among VMs optimally in cloud data centers. In this paper, we have reviewed several existing load balancing mechanisms and we have tried to address the problems associated with them.
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References
[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 Science and 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 Multi Conference 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.
[21] Ankit Kumar, Mala Kalra,†Load Balancing in Cloud Data Center Using Modified Active Monitoring Load Balancerâ€, IEEE pp. 1-5, 2016.
[22] Saraswathi AT, Kalaashri.Y.RA, Dr.S. Padmavathi, “Dynamic Resource Allocation Scheme in Cloud Computingâ€, ELSEVIER, pp. 30-36, 2015.