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Reseach Article

Novel Technique for Load Balancing in Cloud Computing

by Ankita Sharma, Isha Awasthi
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 182 - Number 4
Year of Publication: 2018
Authors: Ankita Sharma, Isha Awasthi
10.5120/ijca2018917523

Ankita Sharma, Isha Awasthi . Novel Technique for Load Balancing in Cloud Computing. International Journal of Computer Applications. 182, 4 ( Jul 2018), 37-40. DOI=10.5120/ijca2018917523

@article{ 10.5120/ijca2018917523,
author = { Ankita Sharma, Isha Awasthi },
title = { Novel Technique for Load Balancing in Cloud Computing },
journal = { International Journal of Computer Applications },
issue_date = { Jul 2018 },
volume = { 182 },
number = { 4 },
month = { Jul },
year = { 2018 },
issn = { 0975-8887 },
pages = { 37-40 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume182/number4/29754-2018917523/ },
doi = { 10.5120/ijca2018917523 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T01:10:24.966268+05:30
%A Ankita Sharma
%A Isha Awasthi
%T Novel Technique for Load Balancing in Cloud Computing
%J International Journal of Computer Applications
%@ 0975-8887
%V 182
%N 4
%P 37-40
%D 2018
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The cloud is the architecture in which virtual machines, data centers, hosts and brokers are involved in the communication. The broker search most reliable virtual machine for the cloudlet execution. In the network uncertainty may happen due to which system get overloaded. In this research, work technique is proposed to increase fault tolerance of the system. The proposed improvement is based on the ACO algorithm which can select the best virtual machine on which cloudlet will be migrated. The performance of the proposed algorithm is testing on cloudsim in terms of execution time, energy consumption. The simulation results demonstrated that execution time and energy consumption of ACO is least as compared to TESA Algorithm. The proposed algorithm can be used for the load balancing in cloud computing.

References
  1. I. Mashal, O. Alsaryrah, T.-Y. Chung, C.-Z. Yang, W.-H. Kuo, and D. P. Agrawal, “Choices for interaction with things on Internet and underlying issues,” Ad Hoc Networks, vol. 28, pp. 68–90, 2015.
  2. O. Said and M. Masud, “Towards internet of things: survey and future vision,” International Journal of Computer Networks, vol. 5, no. 1, pp. 1–17, 2013.
  3. M. Wu, T.-J. Lu, F.-Y. Ling, J. Sun, and H.-Y. Du, “Research on the architecture of internet of thing”, 3rd International Conference on Advanced Computer Theory and Engineering (ICACTE '10), vol. 5, pp. V5-484–V5-487, 2010.
  4. R. Khan, S. U. Khan, R. Zaheer, and S. Khan, “Future internet: the internet of things architecture, possible applications and key challenges,” in Proceedings of the 10th International Conference on Frontiers of Information Technology (FIT '12), vol. 34, pp. 257–260, 2012
  5. S. Tekinay and B. Jabbari, “Handover and channel assignment in mobile cellular networks,” IEEE Communication Magzine, Vol. 29, No. 11, pp. 42-46, 1991.
  6. Deepak Mishra and Swades De, “Energy Harvesting and Sustainable M2M Communication in 5G Mobile Technologies”, Book series on Modeling and Optimization in Science and Technologies, Springer, vol. 8, pp. 99-125, 2016.
  7. Meysam Masoudi, Behzad Khamidehi, and Cicek Cavdar. Green Cloud Computing for Multi Cell Networks. IEEE, 35 (2017), 150-157.
  8. Jagadeeswara Rao. G, G. Stalin Babu. Energy Analysis of Task Scheduling Algorithms in Green Cloud. IEEE International Conference on Innovative Mechanisms for Industry Applications (ICIMIA 2017), vol. 65, pp.302-305, 2017.
  9. Mr. Nitin S. More, Dr. Rajesh B. Ingle, “ Challenges in Green Computing for Energy Saving Techniques”, IEEE 2017 International Conference on Emerging Trends & Innovation in ICT (ICEI), vol. 20, pp. 73-76, 2017.
  10. Ehsan Arianyan, “Multi Objective Consolidation of Virtual Machines for Green Computing in Cloud Data Centers”, IEEE 2016 8th International Symposium on Telecommunications (IST'2016), vol. 27, 654-659, 2016.
  11. Federico Larumbe, Brunilde Sanso, “Green Cloud Broker: On-line Dynamic Virtual Machine Placement Across Multiple Cloud Providers”, 5th IEEE International Conference on Cloud Networking, vol. 34, pp.119-125, 2016.
  12. Chonglin Gu, Pengzhou Shi, Shuai Shi, Hejiao Huang and Xiaohua Jia, “A Tree Regression Based Approach for VM Power Metering”, IEEE ACCESS, vol.70, pp. 610-621, 2015.
Index Terms

Computer Science
Information Sciences

Keywords

Load Balancing Weight-based algorithm Cloud Computing Virtual Machine algorithm