Survey of Load Balancing Methods in Cloud Computing

Authors(3) :-Sachin Shingne, Dr. Umesh K Lilhore, Phiza AmbreenKhan

Now these days cloud computing technology is widely used technology in IT world. Cloud computing serves computing resources as services to cloud users. Cloud computing provides PaaS, IaaS and SaaS services. Cloud uses can be divided in to four major group’s private, public, community and hybrid. Cloud computing reduce cost of ownership. This quality of cloud computing makes it more popular among users. A user can stores their private data over cloud and can access any time. Cloud commuting service are based on “Pay and use based”. Day by day size of cloud users and cloud services are getting increases rapidly. So it is quite challenging for cloud service providers to satisfy cloud user requirement with out and failure in optimum cost. To avoid failure in service and achieved optimum cost various load balancing methods are used. A load balancing is a technique which migrates a job from over loaded machine to an under loaded machine without disturbing current running jobs. In this survey paper we are presenting a review and comparison of various load balancing method suggested by various researchers’ for cloud computing.

Authors and Affiliations

Sachin Shingne
PG Department of Computer Science & Engineering, NRI-IIST Bhopal, Maharashtra, India
Dr. Umesh K Lilhore
PG Department of Computer Science & Engineering, NRI-IIST Bhopal, Maharashtra, India
Phiza AmbreenKhan
PG Department of Computer Science & Engineering, NRI-IIST Bhopal, Maharashtra, India

Cloud computing, load balancing, Performance, optimal utilization, Computing resources

  1. Ashish Gupta, Ritu Garg, "Load Balancing Based Task Scheduling with ACO in Cloud Computing", IEEE international Conference on Computer Applications (ICCA) June 2017, pp 174-180.
  2. K.Sutha, Dr.G.M.Kadhar Nawaz, "Research Perspective of Job Scheduling in Cloud Computing", 2016 IEEE Eighth International Conference on Advanced Computing (ICoAC), April-2016, pp 61-67.
  3. AV. Karthick, Dr.E.Ramaraj, R.Ganapathy Subramanian, An Efficient Multi Queue Job Scheduling for Cloud Computing, IEEE 2014 World Congress on Computing and Communication Technologies, pp. 164-166.
  4. Manisha Patel, Umesh Lilhore," A Survey on Efficient Data Retrieval for Cloud Computing", International Journal of Research in Advent Technology, Vol.5, No.1, January 2017, PP 1-5.
  5. Huankai Chen, Frank Wang, Dr Na Helian, Gbola Akanmu, User-
  6. Priority Guided Min-Min Scheduling Algorithm For Load Balancing in Cloud Computing, IEEE February 2013
  7. Rahul Upadhyay, Umesh lilhore," Review of Various Load Distribution Methods for Cloud Computing, to Improve Cloud Performance", IJCSE, Volume-4, Issue 12, 2016, PP 61-64.
  8. Yichao Yang, Yanbo Zhou, Zhili Sun, Haitham Cruickshank, Heuristic Scheduling Algorithms for Allocation of Virtualized Network and Computing Resources, Journal of Software Engineering and Applications, January 2013, 6, pp. 1-13
  9. Umesh Lilhore, Santosh Kumar, "Advance Anticipatory Performance Improvement Model, for Cloud Computing", International Journal of Recent Trends in Engineering & Research (IJRTER), Volume 02, Issue 08, 2016, PP 210-216.
  10. Ke Liu1, Hai Jin , Jinjun Chen , Xiao Liu , Dong Yuan and Yun Yang, A Compromised-Time-Cost Scheduling Algorithm in SwinDeW-C for Instance-Intensive Cost-Constrained Workflows on a Cloud Computing Platform, The International Journal of High Performance Computing Applications, Volume 24(4) pp. 445-456, May 2010
  11. Umesh Lilhore, Dr. Santosh Kumar," Anticipatory Data Replication Strategy with Dynamic Distributed Model for Cloud Computing", International Journal of Research in Applied Science & Engineering Technology (IJRASET), Volume 4 Issue VIII, August 2016, PP 554-559.
  12. Arash Ghorbannia Delavar, Mahdi Javanmard, Mehrdad Barzegar Shabestari and Marjan Khosravi Talebi, RSDC (Reliable Scheduling Distributed In Cloud Computing), International Journal of Computer Science, Engineering and Applications (IJCSEA) Vol.2, No.3, June 2012
  13. Umesh Lilhore and Dr. Santosh Kumar, "Modified fuzzy logic and advanced particle swarm optimization model for cloud computing", International Journal of Modern Trends in Engineering and Research (IJMTER), Volume 03, Issue 08, August- 2016, PP 230-235.
  14. Nitish Chopra, Sarbjeet Singh, HEFT based Workflow Scheduling Algorithm for Cost Optimization within Deadline in Hybrid Clouds, IEEE - 31661, 4th Computing, Communications and Networking Technologies(ICCCNT) July 4-6, 2013
  15. Umesh Lilhore and Santosh Kumar, "A Novel Performance Improvement Model for Cloud Computing", IJSDR, Volume 1, Issue 8, 2016, 410-412.
  16. Wei Wang, Guosun Zeng, Daizhong Tang, Jing Yao, Cloud-DLS: Dynamic trusted scheduling for Cloud computing, Expert Systems with Applications 39 (2012) pp. 2321-2329 2011 Elsevier Ltd.

Go to Ruwix.com to learn the solution of the Rubik's Cube and other twisty puzzles like Pyraminx, Square-1 etc.

Publication Details

Published in : Volume 3 | Issue 3 | March-April 2018
Date of Publication : 2018-04-30
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 116-121
Manuscript Number : CSEIT1183328
Publisher : Technoscience Academy

ISSN : 2456-3307

Cite This Article :

Sachin Shingne, Dr. Umesh K Lilhore, Phiza AmbreenKhan, "Survey of Load Balancing Methods in Cloud Computing", International Journal of Scientific Research in Computer Science, Engineering and Information Technology (IJSRCSEIT), ISSN : 2456-3307, Volume 3, Issue 3, pp.116-121, March-April-2018.
Journal URL : http://ijsrcseit.com/CSEIT1183328

Article Preview

Follow Us

Contact Us