A Survey: Comparative Study of an Assortment of Load Balancing Algorithms

A Survey: Comparative Study of an Assortment of Load Balancing Algorithms

  IJETT-book-cover  International Journal of Engineering Trends and Technology (IJETT)          
  
© 2017 by IJETT Journal
Volume-46 Number-1
Year of Publication : 2017
Authors : G Gayatri, Dr. P K Vaishali
DOI :  10.14445/22315381/IJETT-V46P203

Citation 

G Gayatri, Dr. P K Vaishali "A Survey: Comparative Study of an Assortment of Load Balancing Algorithms", International Journal of Engineering Trends and Technology (IJETT), V46(1),12-15 April 2017. ISSN:2231-5381. www.ijettjournal.org. published by seventh sense research group

Abstract
Cloud computing refers to control, organizing, and retrieving the applications online. It offers online data storage, infrastructure and application. As Cloud Computing is one of the greatest platform which provides storage of data in very lower cost and obtainable for all time over the internet .Load balancing is one of the main challenges in cloud computing. The objective of load balancing is to dispense the dynamic workload across manifold nodes to certain that no single node is weighed down. To minimize the resource consumption this will further condense energy consumption and carbon emission rate. This paper presents various load balancing algorithms in different cloud environment. And also discussed various metrics and performance parameters that have been considered to judge against different techniques.

 References

1. Vaquero, Luis M., Luis Rodero-Merino, and Rajkumar Buyya. "Dynamically scaling applications in the cloud." ACM SIGCOMM Computer Communication Review 41.1 (2011): 45-52.
2. Ferris, James Michael. "Load balancing in cloud-based networks." U.S. Patent No. 8,849,971. 30 Sep. 2014.
3. Buyya, Rajkumar, Rajiv Ranjan, and Rodrigo N. Calheiros. "Modeling and simulation of scalable Cloud computing environments and the CloudSim toolkit: Challenges and opportunities." High Performance Computing & Simulation, 2009. HPCS`09. International Conference on. IEEE, 2009.
4. Buyya, Rajkumar, Rajiv Ranjan, and Rodrigo N. Calheiros. "Intercloud: Utility-oriented federation of cloud computing environments for scaling of application services." Algorithms and architectures for parallel processing. Springer Berlin Heidelberg, 2010. 13-31.
5. Karger, David R., and Matthias Ruhl. "Simple efficient load balancing algorithms for peer-to-peer systems." Proceedings of the sixteenth annual ACM symposium on Parallelism in algorithms and architectures. ACM, 2004.
6. Randles, Martin, David Lamb, and A. Taleb-Bendiab. "A comparative study into distributed load balancing algorithms for cloud computing." Advanced Information Networking and Applications Workshops (WAINA), 2010 IEEE 24th International Conference on. IEEE, 2010.
7. Congdon, Paul, and Sundar Subramaniam. "Load Balancing Algorithms." (1998).
8. Randles, Martin, David Lamb, and A. Taleb-Bendiab. "A comparative study into distributed load balancing algorithms for cloud computing." Advanced Information Networking and Applications Workshops (WAINA), 2010 IEEE 24th International Conference on. IEEE, 2010.
9. Kansal, Nidhi Jain, and Inderveer Chana. "Cloud load balancing techniques: a step towards green computing." IJCSI International Journal of Computer Science Issues 9.1 (2012): 238-246.
10. Li, Li Erran, and Thomas Woo. "Dynamic load balancing and scaling of allocated cloud resources in an enterprise network." U.S. Patent Application No. 12/571,271.

Keywords
Load balancing, cloud environment, map reduce.