A multi-node adaptive load balancing approach for availability in cloud computing

  • Authors

    • Hamza Kamal idrissi LRIT-CNRST University Mohammed V 4 Avenue Ibn Battouta. BP 1014 RP 10006 Rabat, Morocco
    • Ali Kartit LTI University Chouaïb Doukkali –El Jadida, ENSAJ, Avenue Jabran Khalil Jabran BP 299 El jadida, Morocco
    2018-11-22
    https://doi.org/10.14419/ijet.v7i4.14789
  • Adaptive Load Balancing, Availability, Cloud Computing, Multiple Nodes.
  • Cloud computing has become one of the most important fields in the IT technology domain. Its main objectives are to deliver different services for users, such as infrastructure, platform or software with a reasonable and more and more decreasing cost for the clients. In order to meet those objectives many aspects are studied and are subject to research, the availability is certainly one of the key sides of the Cloud Computing. Load balancing techniques deal with many aspects of the cloud such as performance, response time, … For the big distributed cloud systems that deal with many clients and big amounts of data and requests, load balancing is essential in order to properly satisfy all the demands. In this paper, we address the subject of availability with an adaptive load balancing approach in cloud computing. This proposed approach ensures load balancing as well as the availability of the system while avoiding points of failure.

     

     

     
  • References

    1. [1] K. Nishant, P. Sharma, V. Krishna, C. Gupta, K. P. Singh, Nitin, and R. Rastogi, “Load Balancing of Nodes in Cloud Using Ant Colony Optimization,†presented at the Computer Modelling and Simulation (UKSim), 2012 UKSim 14th International Conference on, 2012, pp. 3–8.

      [2] N. J. Kansal and I. Chana, “Cloud load balancing techniques: A step towards green computing,†IJCSI Int. J. Comput. Sci. Issues, vol. 9, no. 1, pp. 238–246, 2012.

      [3] H. K. Idrissi, A. Kartit, and M. E. Marraki, “FOREMOST SECURITY APPREHENSIONS IN CLOUD COMPUTING,†J. Theor. Appl. Inf. Technol., vol. 59, no. 3, pp. 580–588, Jan. 2014.

      [4] H. Kamal Idrissi, A. Kartit, and M. El Marraki, “A taxonomy and survey of Cloud computing,†presented at the Security Days (JNS3), 2013 National, 2013, pp. 1–5. https://doi.org/10.1109/JNS3.2013.6595470.

      [5] P. Sempolinski and D. Thain, “A Comparison and Critique of Eucalyptus, OpenNebula and Nimbus,†presented at the Cloud Computing Technology and Science (CloudCom), 2010 IEEE Second International Conference on, 2010, pp. 417–426. https://doi.org/10.1109/CloudCom.2010.42.

      [6] A. S. N and M. Hemalatha, “An Approach on Semi-Distributed Load Balancing Algorithm for Cloud Computing System,†Int. J. Comput. Appl., vol. 56, no. 12, pp. 5–10, Oct. 2012.

      [7] R. P. Padhy, “Load balancing in cloud computing systems,†National Institute of Technology, Rourkela, 2011.

      [8] C. Xu and F. C. Lau, Load Balancing in Parallel Computers: Theory and Practice. Norwell, MA, USA: Kluwer Academic Publishers, 1997.

      [9] A. M. Alakeel, “A guide to dynamic load balancing in distributed computer systems,†Int. J. Comput. Sci. Inf. Secur., vol. 10, no. 6, pp. 153–160, 2010.

      [10] M. M. D. Shah, M. A. A. Kariyani, and M. D. L. Agrawal, “Allocation Of Virtual Machines In Cloud Computing Using Load Balancing Algorithm,†Int. J. Comput. Sci. Inf. Technol. Secur. IJCSITS ISSN, pp. 2249–9555, 2013.

      [11] Soumya Ray, “Execution Analysis of Load Balancing Algorithms in Cloud Computing Environment,†Int. J. Cloud Comput. Serv. Archit., vol. 2, no. 5, pp. 1–13, Oct. 2012.

      [12] R. Gupta and R. Bhatia, “An Enhanced and Secure Approach of Load Balancing in Cloud Computing,†2014.

      [13] M. Dash, A. Mahapatra, and N. R. Chakraborty, “Cost Effective Selection of Data Center in Cloud Environment,†Int. J. Adv. Comput. Theory Eng. IJACTE, vol. 2, pp. 2319–2526, 2013.

      [14] S. S. Moharana, R. D. Ramesh, and D. Powar, “Analysis of load balancers in cloud computing,†Int. J. Comput. Sci. Eng., vol. 2, no. 2, pp. 101–108, 2013.

      [15] T. Mathew, K. C. Sekaran, and J. Jose, “Study and analysis of various task scheduling algorithms in the cloud computing environment,†in Advances in Computing, Communications and Informatics (ICACCI, 2014 International Conference on, 2014, pp. 658–664. https://doi.org/10.1109/ICACCI.2014.6968517.

  • Downloads

  • How to Cite

    Kamal idrissi, H., & Kartit, A. (2018). A multi-node adaptive load balancing approach for availability in cloud computing. International Journal of Engineering & Technology, 7(4), 4607-4611. https://doi.org/10.14419/ijet.v7i4.14789