Cloud Computing based on the Load Balancing Algorithm

  • Abstract
  • Keywords
  • References
  • PDF
  • Abstract

    Emerging cloud computing technology is a big step in virtual computing. Cloud computing provides services to clients through the internet. Cloud computing enables easy access to resources distributed all over the world. Increase in the number of the population has further increased the challenge. The main challenge of cloud computing technology is to achieve efficient load balancing. Load balancing is a process of assigning load to available resources in such a way that it avoids overloading of resources. If load balancing is performed efficiently, it improves QoS metric including cost, throughput, response time, resource utilization and performance. Efficient load balancing techniques also provide better user satisfaction. Various load balancing algorithms are used in different scenarios for ensuring the same. In the current research, we will study different algorithms for load balancing and benefits and limitations caused to the system due to the algorithms. In this paper, we will compare static and dynamic load balancing algorithms for various measures of efficiency. These will be useful for future research in the concerned field.


  • Keywords

    Cloud Computing, Load Balancing Algorithms Virtualization, Task allocation, Static and Dynamic Load Balancing.

  • References

      [1] D. Saranya, L. SankaraMaheswari “Load Balancing Algorithms in Cloud Computing: A Review” International Journal of Advanced Research in Computer Science and Software Engineering. Volume 5, Issue 7, July 2015 ISSN: 2277 128X.

      [2] G. Kanmani, E Jayabalan “A survey on recent improved load balancing algorithms in cloud environment” SSRG International Journal of Computer Science and Engineering – NCSACT – 2017 ISSN : 2348-8387.

      [3] Klaithem Al Nuaimi, Nader Mohamed, Mariam Al Nuaimi and Jameela Al-Jaroodi “A Survey of Load Balancing in Cloud Computing: Challenges and Algorithms” 2012 IEEE Second Symposium on Network Cloud Computing and Applications.

      [4] Sidra Aslam, Munam Ali Shah “Load Balancing Algorithms in Cloud Computing: A Survey of Modern Techniques” 2015 National Software Engineering Conference (NSEC 2015).

      [5] T. Deepa Dr. DhanarajCheeluA Comparative Study of Static and Dynamic Load Balancing Algorithms in Cloud International Conference on Energy, Communication, Data Analytics and Soft Computing (ICECDS-2017).

      [6] P. Byuvol, L. Gabsalikhova, I. Makarova, E. Mukhametdinov, G. Sadygova, “Improving the Branded Service Network Efficiency based on its Functioning Evaluation”, Astra Salvensis, Supplement No. 2, p. 373, 2017.

      [7] RatanMishra,AnantJaiswal “Ant colony Optimization: A solution of Load balancing in Cloud. International Journal of Web & Semantic Technology (IJWesT) Vol.3, No.2, April 2012

      [8] Shanti Swaroop Moharana, Raja Deepan D. Ramesh DigamberPowar” Analysis of Load Balancers in Cloud Computing”,Vol.2,Issue.2, (May2013)

      [9] Albert Y. Zomaya, Senior Member, IEEE, Yee-HweiTeh “Observations on Using Genetic Algorithms for Dynamic Load-Balancing”. IEEE TRANSACTIONS ON PARALLEL AND DISTRIBUTED SYSTEMS, VOL. 12, NO. 9, SEPTEMBER 2001.

      [10] Performance Tradeoffs in Static and Dynamic Load Balancing Strategies, NASA March 1986

      [11] Bohn, R. B., Messina, J., Liu, F., Tong J. and Mao J. (2011) ’NIST Cloud Computing Reference Architecture’, IEEE World Congress on Services, 400 Washington, DC, pp. 594–596.

      [12] Tsai, C. W., and Rodrigues, J. J. (2014) ’Metaheuristic scheduling for cloud: A survey’, IEEE Systems Journal, 8(1), pp. 279-291.

      [13] Mishra, S. K., Puthal, D., Sahoo, B., Jena, S. K., and Obaidat, M. S. (2017) ’An adaptive task allocation technique for green cloud computing’, 405 The Journal of Supercomputing, pp. 1-16.

      [14] Ibrahim, A. H., Faheem, H. E. D. M., Mahdy, Y. B., and Hedar, A. R. (2016) ’Resource allocation algorithm for GPUs in a private cloud’, International Journal of Cloud Computing, 5(1-2), pp. 45-56.

      [15] Korolev, A. and Sussman, B., 2000. A technique for habit classification of cloud particles. Journal of Atmospheric and Oceanic Technology, 17(8), pp.1048-1057.

      [16] Helmer, E.H., Kennaway, T.A., Pedreros, D.H., Clark, M.L., Marcano-Vega, H., Tieszen, L.L., Ruzycki, T.R., Schill, S.R. and Sean Carrington, C.M., 2008.

      [17] Li, P., Li, J., Huang, Z., Gao, C.Z., Chen, W.B. and Chen, K., 2017. Privacy-preserving outsourced classification in cloud computing. Cluster Computing, pp.1-10.

      [18] Land cover and forest formation distributions for St. Kitts, Nevis, St. Eustatius, Grenada and Barbados from decision tree classification of cloud-cleared satellite imagery. Caribbean Journal of Science, 44(2), pp.175-198.

      [19] Alonso–Calvo, R., J. Crespo, M. Garc'ia–Remesal, A. Anguita, and V. Maojo (2010) “On Distributing Load in Cloud Computing: A Real Application for Very-large Image Datasets”, Procedia Computer Science (1)1, pp. 2669– 2677, doi: 10.1016/j.procs.2010.04.300.

      [20] American_Society_for_Quality (2006) “Idea Creation Tools―Affinity Diagrams,” (current June 20, 2011).

      [21] Anthes, G. (2010) “Security in the Cloud,” Communications of the ACM (53)11, p. 16. Armando, F. (2011) “Cloud Computing―What’s in It for Me as a Scientist?” Science (331)6016, p. 406

      [22] Banerjee, P., R. Friedrich, C. Bash, P. Goldsack, B.A. Huberman, J. Manley, et al. (2011) “Everything as a Service: Powering the New Information Economy,” Computer (44)3, pp. 36–43.

      [23] Barki, H., S. Rivard, and J. Talbot (1993) “A Keyword Classification Scheme for IS Research Literature: An Update,” MIS Quarterly, June, pp. 209–225.

      [24] Barnhill, D.S. (2010) “Cloud Computing and Stored Communications: Another Look at Quon v. Arch Wireless,” (Privacy Law) (Annual Review of Law and Technology), Berkeley Technology Law Journal (25), pp. 621–648. Bellovin, S.M. (2011) “Clouds from Both Sides, IEEE Security & Privacy (9)3, pp. 88–88

      [25] Currie, C. (2008) “Painting the Clouds,” EDUCAUSE Review (43)6, p. 28.

      [26] Cusumano, M. (2010) “Technology Strategy and Management: Cloud Computing and SaaS as New Computing Platforms,” Communications of the ACM (53)4, pp. 27–29.

      [27] Deelman, E. (2010) "Grids and Clouds: Making Workflow Applications Work in Heterogeneous Distributed Environments," The International Journal of High-Performance Computing Applications (24)3, p. 284.

      [28] Kumar, R. and Charu, S., 2015. An importance of using virtualization technology in cloud computing. Global Journal of Computers & Technology, 1(2).

      [29] Luo, S., Lin, Z., Chen, X., Yang, Z. and Chen, J., 2011, December. Virtualization security for cloud computing service. In Cloud and Service Computing (CSC), 2011 International Conference on (pp. 174-179). IEEE.

      [30] Mijumbi, R., Serrat, J., Gorricho, J.L., Bouten, N., De Turck, F. and Boutaba, R., 2016. Network function virtualization: State-of-the-art and research challenges. IEEE Communications Surveys & Tutorials, 18(1), pp.236-262.

      [31] Azad N., Ghandvar P., Rahimi Z., “Online Search Behaviour of Customers in Shoe Market”, Astra Salvensis, Supplement No. 2, p. 793, 2017.

      [32] Pankaj Sareen, (March 2013) “Cloud Computing: Types, Architecture, Applications, Concerns, Virtualization and Role of IT Governance in Cloud”, International Journal of Advanced Research in Computer Science and Software Engineering, Volume 3, Issue 3, ISSN: 2277 128X.

      [33] [32] Farzad Sabahi, (February 2012) “Secure Virtualization for Cloud Environment Using Hypervisor-based Technology”, International Journal of Machine Learning and Computing, Vol. 2, No. 1.

      [34] Siddharth Jain, Rakesh Kumar, Anamika, Sunil Kumar Jangir, (Dec 2014) "A Comparative Study for Cloud Computing Platform Open Source Software", ABHIYANTRIKI: An International Journal of Engineering & Technology (AIJET), Vol. 1, No. 2, pg: 28-35.

      [35] Rakesh Kumar, Bhanu Bhushan Parashar, (November 2014) "Dynamic Resource Allocation and Management Using OpenStack", National Conference on Emerging Technologies in Computer Engineering (NCETCE) – 2014, Supported by Computer Society Chapter, IEEE Delhi Section.

      [36] Lin, W., Liang, C., Wang, J.Z. and Buyya, R., 2014. Bandwidth‐aware divisible task scheduling for cloud computing. Software: Practice and Experience, 44(2), pp.163-174.

      [37] Robertazzi, T.G., 2003. Ten reasons to use divisible load theory. Computer, 36(5), pp.63-68.

      [38] Kim, S. and Weissman, J.B., 2004, August. A genetic algorithm based approach for scheduling decomposable data grid applications. In Parallel Processing, 2004. ICPP 2004. International Conference on (pp. 406-413). IEEE.

      [39] Takabi, H., Joshi, J.B. and Ahn, G.J., 2010. Security and privacy challenges in cloud computing environments. IEEE Security & Privacy, (6), pp.24-31.

      [40] Zhang, Q., Cheng, L. and Boutaba, R., 2010. Cloud computing: state-of-the-art and research challenges. Journal of internet services and applications, 1(1), pp.7-18.

      [41] Rong, C., Nguyen, S.T. and Jaatun, M.G., 2013. Beyond lightning: A survey on security challenges in cloud computing. Computers & Electrical Engineering, 39(1), pp.47-54.

      [42] Cloud Security Alliance, "Security Guidance for Critical Areas of Focus in Cloud Computing V2.1,"




Article ID: 20528
DOI: 10.14419/ijet.v7i4.7.20528

Copyright © 2012-2015 Science Publishing Corporation Inc. All rights reserved.