Hybrid task scheduling algorithm for high availability in cloud

  • Authors

    • Snehaa K
    • Sivasankari S
    2018-03-19
    https://doi.org/10.14419/ijet.v7i2.8.10490
  • Load balancing, High Availablity, Vm scheduling, task scheduling, cloud computing.

  • Today, wherever we go we will find one thing or the other that is running in cloud. It has become an essential component in our everyday life. Many cloud service providers have been extensively working on improving the performance of the service provided. Highavailability in cloud is a place where various cloud service providers are extensively researching. High availability in cloud can vary depending on the scenario it is considered under. In our case we are going to see this in the form of response time for the request to get processed and how we can improve it. We are proposing an algorithm which will ensure the above and also provide an efficient model for analysing the same. We will also be configuring Reinforcement machine learning algorithm for training the load balancer and the server to process the request faster in a short duration of time.

  • References

    1. [1] Rathore, Neeraj, and Inderveer Chana. "Load balancing and job migration techniques in grid: a survey of recent trends." Wireless personal communications 79, no. 3 (2014): pp 2089-2125.

      [2] Bala, Anju, and Inderveer Chana. "A survey of various workflow scheduling algorithms in cloud environment." In 2nd National Conference on Information and Communication Technology (NCICT),pp. 26-30. sn, 2011.

      [3] Burya R Raman, R. Calheiros, R.N.(2009) “Modeling and Simulation of Scalable Cloud Environment and the Cloud Sim Toolkit: Challenges and Opportunities’’, IEEE publication 2009,pp1-11

      [4] â€Network Load Balancer â€https://technet.microsoft.com/en-us/ library/cc725691(v=ws.11).aspx

      [5] “Server Clustering â€https://wordframe.com/docs/wiki/server-cluster-definition

      [6] Zou S. (2012) Analysis and Algorithm of Load Balancing Strategy of the Web Server Cluster System. In: Zhao M., Sha J. (eds)Communications and Information Processing.Communications in Computer and Information Science, vol 289. Springer, Berlin, Heidelberg.

      [7] Dr.SudhaSadhasivam, R. Jayarani, Dr. N. Nagaveni, R. Vasanth Ram “Design and Implementation of an efficient Twolevel Scheduler for Cloud Computing Environment†In Proceedings of International Conference on Advances in Recent Technologies in Communication and Computing, 2009

      [8] G. Guo-Ning and H. Ting-Lei, “Genetic Simulated Annealing Algorithm for Task Scheduling based on Cloud Computing Environment,†In Proceedings of International Conference on Intelligent Computing and Integrated Systems, 2010, pp. 60-63

      [9] Jasmin James, Dr.BhupendraVerma “Efficient Vm Load BalancinAlgorithim For A Cloud Computing Environment †In Proceeding of International Journal on Computer Science and Engineering (IJCSE) Vol. 4 No. 09, Sep 2012

      [10] Dr. Amit Agarwal, Saloni Jain “Efficient Optimal Algorithm of Task Scheduling in Cloud Computing Environment†In International Journal of Computer Trends and Technology (IJCTT) – volume 9 number 7– Mar 2014

      [11] G. T. Hicham, EL.Chaker, Cloud Computing CPU Allocation and Scheduling Algorithms using CloudSim Simulator, International Journal of Electrical and Computer Engineering, Vol 6, No 4, 2016

      [12] Dorigo, M., Gambardella, L.M.: Ant colony system: a cooperative learning approach to the traveling salesman problem. IEEE Trans. Evol. Comput. 1(1), pp53–66 (1997).

      [13] S.V.Manikanthan and V.Rama“Optimal Performance of Key Predistribution Protocol In Wireless Sensor Networks†International Innovative Research Journal of Engineering and Technology ,ISSN NO: 2456-1983,Vol-2,Issue –Special –March 2017.

      [14] T. Padmapriya and V.Saminadan, “Handoff Decision for Multi-user Multiclass Traffic in MIMO-LTE-A Networksâ€, 2nd International Conference on Intelligent Computing, Communication & Convergence (ICCC-2016) – Elsevier - PROCEDIA OF COMPUTER SCIENCE, vol. 92, pp: 410-417, August 2016.

  • Downloads

  • How to Cite

    K, S., & S, S. (2018). Hybrid task scheduling algorithm for high availability in cloud. International Journal of Engineering & Technology, 7(2.8), 455-490. https://doi.org/10.14419/ijet.v7i2.8.10490