Review on failure forecast in cloud for a fault tolerant system

  • Authors

    • J M. Nandhini
    • T Gnanasekaran
    2018-06-08
    https://doi.org/10.14419/ijet.v7i2.33.13857
  • Fault Tolerance, Virtualization, Checkpoint, Fault Prediction
  • Cloud Computing is an increasingly popular computer paradigm constituting a large infrastructure involving storage, memory, servers and applications accessible via computer network. The cloud system design aims to provide on-demand services with scalability on diverse resources to ensure efficient resource utilization in addition to effectiveness. As cloud is a service-oriented infrastructure, it is critically imperative that the system is highly reliable to meet the Service Level Agreement (SLA). To achieve reliability, cloud requires a very efficient fault tolerance mechanism. Serviceability and reliability is impacted by any failure in the system. Prior prediction of faults in the system helps in overcoming failures. The Fault Tolerance in cloud involves ascertaining the resource fitness to execute scheduled task. The process involves prior screening of resources against various tasks as part of scheduling process. The scheduling process relies significantly on the virtualization of resources to maintain high efficiency.

     

  • References

    1. [1] https://arxiv.org/pdf/1507.03562.pdf.

      [2] Paul Townend, Jie Xu, Fault tolerance within a grid environment, as part of the e-Demand project at the University Of Durham, DH1, United Kingdom, 2003.

      [3] P. Latchoumy and P. Sheik Abdul Khader , “Survey On Fault Tolerance In Grid Computingâ€, in International Journal of Computer Science & Engineering Survey (IJCSES) Vol.2, No.4, November 2011.

      [4] Bala, A., & Chana, I. (2012).†Fault Tolerance-Challenges, Techniques and Implementation in Cloud Computingâ€, International Journal of Computer Science Issues (IJCSI), 9(1).

      [5] N. Shahapure and P. Jayarekha, Load balancing with optimal cost scheduling algorithm," in International Conference on Computation of Power, Energy, Information and Communication (ICCPEIC), pages 24-31, (2014).

      [6] Alain Tchana, Laurent Broto, Daniel Hagimon. (2012). Approaches to Cloud Computing Fault Tolerance, 978-1-4673-1550-0/ 12, IEEE.

      [7] PFT-CCKP: A Proactive Cloud Services Fault Tolerance Mechanism Jialei Liu Shangguang Wang, Ao Zhou, Fangchun Yang State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications Beijing, China.

      [8] B Jing Liu, Jiantao Zhou and Rajkumar Buyya, Software Rejuvenation based Fault Tolerance Scheme forcloud.

      [9] Purvil Bambharolia, Prajeet Bhavsar, Vivek Prasad, Failure Prediction and Detection in Cloud Datacenters, International Journal of Scientific & Technology Research Volume 6, Issue 09, September 2017.

      [10] Shafi’i Muhammad Abdulhami, Muhammad Shafie Abd Latiff, Syed Hamid Hussain Madni, Mohammed Abdullahi, Fault tolerance aware scheduling technique for Cloud Applications .2015 IEEE 8th International Conference on Cloud Computing.

      [11] Ifeanyi P. Egwutuoha, Shiping Chen, David Levy,Bran Selic, Rafael Calvo, A Proactive Fault Tolerance Approach to High Performance Computing (HPC) in the Cloud, 2012 Second International Conference on Cloud and Green ComputingIEEE 2012.

      [12] Ravi Jhawar,, Vincenzo Piuri, Marco Santambrogio , A Comprehensive Conceptual System-Level Approach to Fault Tolerance in Cloud Computing.

      [13] Zhao, W., Melliar,Smith, P. M., & Moser, L. E. (2010, July). Fault tolerance middleware for cloud computing. In Cloud Computing (CLOUD), 2010 IEEE 3rd International Conference on (pp. 67-74). IEEE.

      [14] Sheheryar Malik, Fabrice Huet IEEE World Congress on Services, Jul 2011, Adaptive Fault Tolerance in Real Time Cloud Computing.

      [15] Geoffroy Vallee, Kulathep Charoenporn wattana, Christian Engelmann, AnandTikotekar, Stephen L. Scott,†A Framework for Proactive Fault Toleranceâ€.

      [16] Dawei Sun,Guiran Chang,Changsheng Miao,Xingwei Wang, Analyzing, modeling and evaluating dynamic adaptive fault tolerance strategies in cloud computing environments, https://link.springer.com/journal/11227">The Journal of Supercomputing.

  • Downloads

  • How to Cite

    M. Nandhini, J., & Gnanasekaran, T. (2018). Review on failure forecast in cloud for a fault tolerant system. International Journal of Engineering & Technology, 7(2.33), 67-70. https://doi.org/10.14419/ijet.v7i2.33.13857