CFP last date
20 December 2024
Call for Paper
January Edition
IJCA solicits high quality original research papers for the upcoming January edition of the journal. The last date of research paper submission is 20 December 2024

Submit your paper
Know more
The week's pick
Responsive image
Improved Shuffled Frog Leaping Algorithm with Self-Adaptive Shuffling for Fuzzy Logic PD+G Controller Optimization in Robotic Manipulators

Duc Hoang Nguyen
Random Articles
Reseach Article

Systematic Review on Existing Load Balancing Techniques in Cloud Computing

by Danlami Gabi, Abdul Samad Ismail, Anazida Zainal
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 125 - Number 9
Year of Publication: 2015
Authors: Danlami Gabi, Abdul Samad Ismail, Anazida Zainal
10.5120/ijca2015905539

Danlami Gabi, Abdul Samad Ismail, Anazida Zainal . Systematic Review on Existing Load Balancing Techniques in Cloud Computing. International Journal of Computer Applications. 125, 9 ( September 2015), 16-24. DOI=10.5120/ijca2015905539

@article{ 10.5120/ijca2015905539,
author = { Danlami Gabi, Abdul Samad Ismail, Anazida Zainal },
title = { Systematic Review on Existing Load Balancing Techniques in Cloud Computing },
journal = { International Journal of Computer Applications },
issue_date = { September 2015 },
volume = { 125 },
number = { 9 },
month = { September },
year = { 2015 },
issn = { 0975-8887 },
pages = { 16-24 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume125/number9/22459-2015905539/ },
doi = { 10.5120/ijca2015905539 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:16:06.516107+05:30
%A Danlami Gabi
%A Abdul Samad Ismail
%A Anazida Zainal
%T Systematic Review on Existing Load Balancing Techniques in Cloud Computing
%J International Journal of Computer Applications
%@ 0975-8887
%V 125
%N 9
%P 16-24
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Cloud computing requires more reliable, efficient and scalable load balancing algorithm to survive. As one of the main challenges in cloud computing, load balancing facilitate dynamic workload across multiple nodes ensuring that no single node get overloaded. With proper load balancing, resource consumption is maintained at minimum level, enabling scalability, avoiding bottleneck and overprovisioning etc. In this paper, systematic review on existing load balancing techniques currently prevalent in cloud computing was carried out. Load balancing metrics; Response time, Performance, Resource Utilization, Throughput, Cost Overhead, Scalability, Fault Tolerant and Migration Time were used to evaluate the existing techniques. Findings show that the existing techniques mainly focus on reducing response time, completion time, cost and improving throughput. Neither of the techniques was able to unveil efficient load balancing of task scheduling for single and federated cloud environment. However, research such as load balancing of energy consumption, server consolidation, Virtual Machine Migration, are not taken into consideration by the existing techniques. Future research is to unveil efficient multi-objective load balancing of tasks scheduling algorithm with quality of service improvements for homogeneous and federated heterogeneous cloud environment.

References
  1. Ashwin, T. S., Domanal, S. G. and Guddeti, R. M. R. 2014. A Novel Bio-Inspired Load Balancing of Virtual Machines in Cloud Environment. In Proceedings of the IEEE International Conference on Cloud Computing in Emerging Networks (CCEM). 15- 17 October. Bangalore, India, 1-4.
  2. Bagwaiya, V. and Raghuwanshi, S. K. 2014. Hybrid Approach Using Throttled and ESCE Load Balancing Algorithms in Cloud Computing. In Proceedings of the International Conference on Green Computing Communication and Electric Engineering (ICGCCEE). 6-8 March. Coimbatore, India, 1-6.
  3. Bagwaiya, V. and Raghuwanshi, S. K. 2014. Hybrid Approach Using Throttled and ESCE Load Balancing Algorithms in Cloud Computing. In Proceedings of the International Conference on Green Computing Communication and Electric Engineering (ICGCCEE). 6-8 March. Coimbatore, India, 1-6.
  4. Dhinesh, B, L. D. and Krishna, P. V. “Honey Bee Behavior Inspired Load Balancing of Tasks in Cloud Computing Environments”, Journal of Applied Soft Computing, 2013, 13(5), pp. 2292-2303.
  5. Domanal, G. S. and Reddy, G. R. M. 2014. Optimal Load Balancing in Cloud Computing by Efficient Utilization of Virtual Machines. In Proceedings of the Sixth International Conference on Communication Systems and Networking (COMSNETS). 6-10 January. Banglore, India, 1-4.
  6. Effatparvara,M. and Garshasbi, M. S. “A Genetic Algorithm for Static Load Balancing in Parallel Heterogeneous Systems”, Procedia - Social and Behavioural Sciences,Jornal, 2014, 129, 358 – 364.
  7. Fahim, Y., Lahmar, E. B., Labrlji, E. and Eddaoui, A. 2014. The Load Balancing Based on the Estimated Finish Time of Tasks in Cloud Computing. In Proceedings of the Second World Conference on Complex Systems (WCCS). 10-12 November. Agadir, Morocco, 594-598.
  8. Hao, Y. Liu, G. and Lu, J. “Three Levels Load Balancing on Cloud”, International Journal of Grid Distribution Computing, 2014, 7(3), pp. 71-88.
  9. Haidri, R. A., Katti, C. P. and Saxena, P. C. 2014. A Load Balancing Strategy for Cloud Computing Environment. In Proceedings of the 2014 International Conference on Signal Propagation and Computer Technology (ICSPCT). 12-13 July. Ajmer, India, 636-641.
  10. Hassan, M. M., Song, B. and Huh, E-N. 2011. Distributed Resource allocation Games in Horizontal Dynamic Cloud Federated platform. In Proceedings of the IEEE International Conference on High Performance Computing and Communications. 2-4 September. Banff, Canada, 822-827.
  11. Kansal, N. J. and Chana, A. J. “Existing Load Balancing Techniques in Cloud Computing: A Systematic Review”, Journal of Information Systems and Communication, 2012, 3(1), 87-91.
  12. Katyal, M. and Mishra, A. “A Comparative Study of Load Balancing Algorithm in Cloud Computing Environment”, International Journal of Distributed and Cloud Computing, 2012, 1(2), 5-14.
  13. Katyal, M. and Mishra, A. “Application of Selective Algorithm for Effective Resource Provisioning In Cloud Computing Environment”, International Journal on Cloud Computing: Service and Architecture (IJCCSA), 2014, 4(1), 1-10.
  14. Malhotra, M. and Singh, A. 2014. Adaptive Framework for Load Balancing to Improve the Performance of Cloud Environment. In Proceedings of the IEEE International Conference on Computational Intelligence and Communication Technology (CICT). 13-14 February. Ghaziabad, India, 224-228.
  15. Ramezani, F., Jie Lu, J. and Hussain, F. K. “Task-Based System Load Balancing in Cloud Computing Using Particle Swarm Optimization”, International Journal of Parallel Programming, 2014, 42, 739-754.
  16. Sharma, T. and Banga, V. K. “Efficient and Enhanced Algorithm in Cloud Computing”, International Journal of Soft Computing and Engineering (IJSCE), 2013, 3(1), 385-219.
  17. Shahapure, N. H. and Jayarekha, P. 2014. Load Balancing with Optimal Cost Scheduling Algorithm. In Proceedings of the International Conference on Computation of Power, Energy, Information and communication (ICCPEIC). 16-17 April. Chennai, India, 24-31.
  18. Sheeja, Y. S. and Jayalekshmi, S. 2014. Cost Effective Load Balancing Based on Honey bee Behaviour in Cloud Environment. In Proceedings of the First International Conference on Computational System and Communication (ICCSC). 17-18 December. Trvandrum, India, 214-219.
  19. Silpa, C. S. and Basha, M. S. S. “A Comparative Analysis of Scheduling Policies in Cloud Computing Environment”, International Journal of Computer Applications, 2013, 67(20), 16-24.
  20. Singh, A., Juneja, D. and Malhotra, M. 2015. “Autonomous Agent Based Load Balancing Algorithm in Cloud Computing”, Procedia Computer Science journal, 2015, 45(1), 832-841.
  21. Shobana, G., Geetha, M. and Suganthe, R. C. 2014. Nature Inspired Preemptive Task Scheduling for Load Balancing in Cloud Datacenter. In Proceeding of the International Conference on Information Communication and Embedded Systems (ICICES). 27-28 February. Chennai, India, 1-6.
  22. Soni, G. and Kalra, M. 2014. A Novel Approach for Load Balancing in Cloud Data Centre. In Proceedings of the IEEE International Conference on Advance Computing Conference (IACC). 21-22 February. Gurgaon, India, 807-812.
  23. Sreenivas, V. Prathap, M. and Kemal, M. 2014. Load Balancing Techniques: Major Challenge in Cloud Computing – A Systematic Review. In Proceedings of the International Conference on Electronic and Communication System (ICECS). 13-14 February. Coimbatore, India, 1-6.
  24. Sun, H., Zhao, T., Tang, Y. and Liu, X. 2014. A QoS-aware Load Balancing Policy in Multi-tenancy Environment. In Proceedings of the 8th International Symposium on Service Oriented System Engineering. 7-11 April. Oxford, United Kingdom, 140-147.
  25. Xu, X., Yu, H. and Cong, X. 2013. A QoS-constrained Resource Allocation Game in Federated Cloud. In Proceedings of the 2013 Seventh International Conference on Innovative Mobile and Internet Services in Ubiquitous Computing. 3-5 July. Asia University, Taichung, Taiwan, 268-275.
Index Terms

Computer Science
Information Sciences

Keywords

Cloud Computing Load Balancing Task Scheduling Federated Cloud.

Powered by PhDFocusTM