An Enhanced Load Balancing Technique for Efficient Load Distribution in Cloud-Based IT Industries

  • Rashmi KrishnaIyengar Srinivasan
  • V. Suma
  • Vaidehi Nedu
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 182)


The advent of technology has led to the emergence of new technologies such as cloud computing. Evolution of IT industry has oriented towards the consumption of large scale infrastructure and development of optimal software products, thereby demanding heavy capital investment by the organizations. Cloud computing is one of the upcoming technologies that have enabled to allocate apt resources on demand in a pay-go approach. However, the existing techniques of load balancing in cloud environment are not efficient in reducing the response time required for processing the requests. Thus, one of the key challenges of the state-of- art of research in cloud is to reduce the response time, which in turn reduces starvation and job rejection rates. This paper, therefore aims to provide an efficient load balancing technique that can reduce the response time to process the job requests that arrives from various users of cloud. An enhanced Shortest Job First Scheduling algorithm, which operates with threshold (SJFST), is used to achieve the aforementioned objective. The simulation results of this algorithm shows the realization of efficient load balancing technique which has resulted in reduced response time leading to reduced starvation and henceforth lesser job rejection rate. This enhanced technique of SJFST proves to be one of the efficient techniques to accelerate the business performance in cloud atmosphere.


Cloud Computing Virtualization Response Time Starvation Job Rejection Load Balancing 


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  1. 1.
    Meng, X., et al.: Efficient Resource Provisioning in Compute Clouds via VM Multiplexing. In: ICAC 2010, Washington, DC, USA, June 7-11 (2010), ©2010 ACM 978-1-4503-0074-2/10/06Google Scholar
  2. 2.
    Wee, S., Liu, H.: Client-side Load Balancer using Cloud. In: SAC 2010, Sierre, Switzerland, March 22-26 (2010) © 2010 ACM 978-1-60558-638-0/10/03Google Scholar
  3. 3.
    Wang, S.-C., et al.: Towards a Load Balancing in a Three-level Cloud Computing Network. In: 3rd IEEE Conference on Computer Science and Information Technology (ICCSIT), pp. 108–113 (2010)Google Scholar
  4. 4.
    Hu, J., et al.: A scheduling strategy on load balancing of virtual machine resources in cloud computing environment. In: 3rd International Symposium on Parallel Architectures, Algorithms and Programming, pp. 89–96 (2010)Google Scholar
  5. 5.
    Tian, W., et al.: A Dynamic and Integrated Load balancing Scheduling Algorithm for Cloud Datacenters. In: Proc. IEEE CCIS 2011, pp. 311–315 (2011)Google Scholar
  6. 6.
    Nae, V., et al.: Cost-Efficient Hosting and Load Balancing of Massively Multiplayer Online Games. In: 11th IEEE/ACM International Conference on Grid Computing, pp. 9–16 (2010)Google Scholar
  7. 7.
    Chen, S., et al.: Secondary Job Scheduling in the Cloud with Deadlines. In: IEEE International Symposium on Parallel and Distributed Processing Workshops and PhD Forum (2011)Google Scholar
  8. 8.
    Gopalakrishnan Nair, T.R., Vaidehi, M., Rashmi, K.S., Suma, V.: An Enhanced Scheduling Strategy to Accelerate the Business Performance of the Cloud System. In: Satapathy, S.C., Avadhani, P.S., Abraham, A. (eds.) Proceedings of the InConINDIA 2012. AISC, vol. 132, pp. 461–468. Springer, Heidelberg (2012)Google Scholar
  9. 9.
    Lee, R., Jeng, B.: Load Balancing Tactics in Cloud. In: International Conference on Cyber-Enabled Distributed Computing and Knowledge Discovery (CyberC), pp. 447–454 (2011)Google Scholar
  10. 10.
    Jin, J., et al.: BAR: An Efficient Data Locality Driven Task Scheduling Algorithm for Cloud Computing. In: 11th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing, pp. 295–304 (2011)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Rashmi KrishnaIyengar Srinivasan
    • 1
  • V. Suma
    • 2
    • 3
  • Vaidehi Nedu
    • 2
    • 3
  1. 1.Post Graduate Programme, Computer Science and Engineering, Department of Information Science and EngineeringDayananda Sagar College of EngineeringBangaloreIndia
  2. 2.Research and Industry Incubation CenterDayananda Sagar InstitutionsBangaloreIndia
  3. 3.Department of Information Science and EngineeringDayananda Sagar College of EngineeringBangaloreIndia

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