Advertisement

Design and Implementation of an Improved Datacenter Broker Policy to Improve the QoS of a Cloud

  • Tamojit Chatterjee
  • Varun Kumar Ojha
  • Mainak Adhikari
  • Sourav Banerjee
  • Utpal Biswas
  • Václav Snášel
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 303)

Abstract

Cloud Computing offers various remotely accessible services to users either free or on payment. A major issue with Cloud Service Providers (CSP) is to maintain Quality of Service (QoS). The QoS encompasses different parameters, like, smart job allocation strategy, efficient load balancing, response time optimization, reduction in wastage of bandwidth, accountability of the overall system, best Virtual Machine (VM) (which reduce the overall execution time of the requested Cloudlets) selection etc. The Datacenter Broker (DCB) policy helps binding a Cloudlet with a VM. An efficient DCB policy reduces the overall execution time of a Cloudlet. Allocating cloudlets properly to the appropriate VMs in a Datacenter makes a system active, alive and balanced. In present study, we proposed a conductance algorithm for effective allocation of Cloudlets to the VMs in a Datacenter by taking into consideration of power and capacity of VMs, and length of Cloudlets. Experimental results obtained using CloudSim toolkit under heavy loads, establishes performance supremacy of our proposed algorithm over existing DCB algorithm.

Keywords

Cloud Computing Quality of Service Cloud Service Provider Virtual Machine Datacenter Datacenter Broker 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Xiong, K., Perros, H.: Service Performance and Analysis in Cloud Computing, pp. 693–700, $25.00 © 2009 IEEE (2009) 978-0-7695- 3708-5/09Google Scholar
  2. 2.
    Sotomayor, B., Montero, R.S., Llorente, I.M., Foster, I.: Virtual Infrastructure Management in Private and Hybrid Clouds, 1089-7801/09/$26.00 © 2009 IEEE (2009)Google Scholar
  3. 3.
    Armbrust, M., Fox, A., Griffith, R., Joseph, A., Katz, R., Konwinski, A., Lee, G., Patterson, D., Rabkin, A., Stoica, I., Zaharia, M.: A Berkeley View of Cloud computing. Technical Report No. UCB/EECS-2009-28, University of California at Berkley, USA (February 10, 2009)Google Scholar
  4. 4.
    Aymerich, F.M., Fenu, G., Surcis, S.: An Approach to a Cloud Computing Network, pp. 113–118. ©2008 IEEE (2008) 978-1-4244-2624- 9/08/$25.00Google Scholar
  5. 5.
    Lei, X., Zhe, X., Shaowu, M., Xiongyan, T.: Cloud Computing and Services Platform Construction of Telecom Operator. In: 2nd IEEE International Conference on Digital Object Identifier, Broadband Network & Multimedia Technology, IC-BNMT 2009, pp. 864–867 (2009)Google Scholar
  6. 6.
    Adhikari, M., Banerjee, S., Biswas, U.: Smart Task Assignment Model for Cloud Service Provider. Special Issue of International Journal of Computer Applications (0975 – 8887) on Advanced Computing and Communication Technologies for HPC Applications - ACCTHPCA (June 2012)Google Scholar
  7. 7.
    Buyya, R., Ranjan, R., Calheiro, R.N.: Modeling and Simulation of scalable Cloud Computing Environments and the CloudSim Toolkit: Challenges and OpportunitiesGoogle Scholar
  8. 8.
    Parsa, S., Entezari-Maleki, R.: RASA: A New Grid Task Scheduling Algorithm. International Journal of Digital Content Technology and its Applications 3, 91–99 (2009)Google Scholar
  9. 9.
    Brucker, P.: Scheduling Algorithms, 5th edn. Springer Press (2007)Google Scholar
  10. 10.
    George Amalarethinam, D.I., Muthulakshmi, P.: An Overview of the scheduling policies and algorithms in Grid Computing. International Journal of Research and Reviews in Computer Science 2(2), 280–294 (2011)Google Scholar
  11. 11.
    El-kenawy, E.-S.T., El-Desoky, A.I., Al-rahamawy, M.F.: Extended Max-Min Scheduling Using Petri Net and Load Balancing. International Journal of Soft Computing and Engineering (IJSCE) 2(4), 2231–2307 (2012) ISSN: 2231-2307Google Scholar
  12. 12.
    Mohammad Khanli, L., Analoui, M.: Resource Scheduling in Desktop Grid by Grid-JQA. In: The 3rd International Conference on Grid and Pervasive Computing. IEEE (2008)Google Scholar
  13. 13.
    White Paper- VMware Infrastructure Architecture Overview, VMwareGoogle Scholar
  14. 14.
    Yang, J., Khokhar, A., Sheikht, S., Ghafoor, A.: Estimating Execution Time For Parallel Tasks in Heterogeneous Processing (HP) Environment. 1994 IEEE (1994) 0-8186-5592-5194 $3.00 QGoogle Scholar
  15. 15.
    Amalarethinam, D.I.G., Selvi, F.K.M.: A Minimum Makespan Grid Workflow Scheduling Algorithm. © 2012 IEEE (2012) 978-1-4577-1583-9/ 12/ $26.00Google Scholar
  16. 16.
    Belalem, G., Tayeb, F.Z., Zaoui, W.: Approaches to Improve the Resources Management in the Simulator CloudSim. In: Zhu, R., Zhang, Y., Liu, B., Liu, C. (eds.) ICICA 2010. LNCS, vol. 6377, pp. 189–196. Springer, Heidelberg (2010)CrossRefGoogle Scholar
  17. 17.
    Bhatia, W., Buyya, R., Ranjan, R.: CloudAnalyst: A CloudSimbased Visual Modeller for Analysing Cloud Computing Environments and Applications. In: 2010 24th IEEE International Conference on Advanced Information Networking and Applications, pp. 446–452 (2010)Google Scholar
  18. 18.
    Calheiros, R.N., Ranjan, R., De Rose, C.A.F., Buyya, R.: CloudSim: A Novel Framework for modelling and Simulation of Cloud Computing Infrastructures and Services (2009)Google Scholar
  19. 19.
    Calheiros, R.N., Ranjan, R., De Rose, C.A.F., Buyya, R.: CloudSim: A Novel Framework for Modeling and Simulation of Cloud Computing Infrastructures and Services. Technical Report, GRIDS-TR-2009-1, Grid Computing and Distributed Systems Laboratory, The University of Melbourne, Australia (2009)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Tamojit Chatterjee
    • 1
  • Varun Kumar Ojha
    • 2
  • Mainak Adhikari
    • 3
  • Sourav Banerjee
    • 1
  • Utpal Biswas
    • 4
  • Václav Snášel
    • 2
  1. 1.Dept. of Computer Science & EngineeringKalyani Govt. Engineering CollegeKalyaniIndia
  2. 2.IT4InnovationsVSB Technical University of OstravaOstravaCzech Republic
  3. 3.Dept. of Computer Science & Engg.IMPS College of Engineering and TechnologyMaldaIndia
  4. 4.Dept. of Computer Science & Engg.University of KalyaniKalyaniIndia

Personalised recommendations