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Review on Fault Tolerance Techniques in Cloud Computing

by Zeeshan Amin, Harshpreet Singh, Nisha Sethi
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 116 - Number 18
Year of Publication: 2015
Authors: Zeeshan Amin, Harshpreet Singh, Nisha Sethi
10.5120/20435-2768

Zeeshan Amin, Harshpreet Singh, Nisha Sethi . Review on Fault Tolerance Techniques in Cloud Computing. International Journal of Computer Applications. 116, 18 ( April 2015), 11-17. DOI=10.5120/20435-2768

@article{ 10.5120/20435-2768,
author = { Zeeshan Amin, Harshpreet Singh, Nisha Sethi },
title = { Review on Fault Tolerance Techniques in Cloud Computing },
journal = { International Journal of Computer Applications },
issue_date = { April 2015 },
volume = { 116 },
number = { 18 },
month = { April },
year = { 2015 },
issn = { 0975-8887 },
pages = { 11-17 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume116/number18/20435-2768/ },
doi = { 10.5120/20435-2768 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:57:28.411450+05:30
%A Zeeshan Amin
%A Harshpreet Singh
%A Nisha Sethi
%T Review on Fault Tolerance Techniques in Cloud Computing
%J International Journal of Computer Applications
%@ 0975-8887
%V 116
%N 18
%P 11-17
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

With the immense growth of internet and its users, Cloud computing, with its incredible possibilities in ease, Quality of service and on-interest administrations, has turned into a guaranteeing figuring stage for both business and non-business computation customers. It is an adoptable technology as it provides integration of software and resources which are dynamically scalable. The dynamic environment of cloud results in various unexpected faults and failures. The ability of a system to react gracefully to an unexpected equipment or programming malfunction is known as fault tolerance. In order to achieve robustness and dependability in cloud computing, failure should be assessed and handled effectively. Various fault detection methods and architectural models have been proposed to increase fault tolerance ability of cloud. The objective of this paper is to propose an algorithm using Artificial Neural Network for fault detection which will overcome the gaps of previously implemented algorithms and provide a fault tolerant model.

References
  1. Foster, I. , Zhao, Y. , Raicu, I. , & Lu, S. (2008, November). Cloud computing and grid computing 360-degree compared. In Grid Computing Environments Workshop, 2008. GCE'08 (pp. 1-10). Ieee.
  2. Mell, P. , & Grance, T. (2009). The NIST definition of cloud computing. National Institute of Standards and Technology, 53(6), 50.
  3. Plummer, D. C. , Cearley, D. W. , & Smith, D. M. (2008). Cloud computing confusion leads to opportunity. Gartner Report.
  4. Gong, C. , Liu, J. , Zhang, Q. , Chen, H. , & Gong, Z. (2010, September). The characteristics of cloud computing. In Parallel Processing Workshops (ICPPW), 2010 39th International Conference on (pp. 275-279). IEEE.
  5. Carolan, S. J. (2009). Introduction to cloud computing. Architecture. White Paper, 1st edn. Sun Microsystems (June 2009).
  6. Furht, B. (2010). Cloud computing fundamentals. In Handbook of cloud computing (pp. 3-19). Springer US.
  7. Kaushal, V. , & Bala, A. (2011). Autonomic fault tolerance using haproxy in cloud environment. Int. J. of Advanced Engineering Sciences and Technologies, 7(2), 54-59.
  8. Patra, P. K. , Singh, H. , & Singh, G. (2013). Fault Tolerance Techniques and Comparative Implementation in Cloud Computing. International Journal of Computer Applications, 64(14).
  9. Bala, A. , & Chana, I. (2012). Fault Tolerance-Challenges, Techniques and Implementation in Cloud Computing. International Journal of Computer Science Issues (IJCSI), 9(1).
  10. Tchana, A. , Broto, L. , & Hagimont, D. (2012, March). Fault Tolerant Approaches in Cloud Computing Infrastructures. In ICAS 2012, The Eighth International Conference on Autonomic and Autonomous Systems (pp. 42-48).
  11. Hayashibara, N. , Defago, X. , Yared, R. , & Katayama, T. (2004, October). The ? accrual failure detector. In Reliable Distributed Systems, 2004. Proceedings of the 23rd IEEE International Symposium on (pp. 66-78). IEEE.
  12. Gupta, I. , Chandra, T. D. , & Goldszmidt, G. S. (2001, August). On scalable and efficient distributed failure detectors. In Proceedings of the twentieth annual ACM symposium on Principles of distributed computing (pp. 170-179). ACM
  13. Maier, G. , Sommer, R. , Dreger, H. , Feldmann, A. , Paxson, V. , & Schneider, F. (2008, August). Enriching network security analysis with time travel. In ACM SIGCOMM Computer Communication Review (Vol. 38, No. 4, pp. 183-194). ACM.
  14. Bahl, P. , Chandra, R. , Greenberg, A. , Kandula, S. , Maltz, D. A. , & Zhang, M. (2007, August). Towards highly reliable enterprise network services via inference of multi-level dependencies. In ACM SIGCOMM Computer Communication Review (Vol. 37, No. 4, pp. 13-24). ACM.
  15. Chen, W. , Toueg, S. , & Aguilera, M. K. (2002). On the quality of service of failure detectors. Computers, IEEE Transactions on, 51(5), 561-580.
  16. Bertier, M. , Marin, O. , & Sens, P. (2002). Implementation and performance evaluation of an adaptable failure detector. In Dependable Systems and Networks, 2002. DSN 2002. Proceedings. International Conference on (pp. 354-363). IEEE.
  17. Bertier, M. , Marin, O. , & Sens, P. (2003, June). Performance analysis of a hierarchical failure detector. In 2013 43rd Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN) (pp. 635-635). IEEE Computer Society.
  18. Défago, X. , Urbán, P. , Hayashibara, N. , & Katayama, T. (2005, March). Definition and specification of accrual failure detectors. In Dependable Systems and Networks, 2005. DSN 2005. Proceedings. International Conference on (pp. 206-215). IEEE.
  19. A Vouk, M. (2008). Cloud computing–issues, research and implementations. CIT. Journal of Computing and Information Technology, 16(4), 235-246.
  20. Jhawar, R. , Piuri, V. , & Santambrogio, M. (2013). Fault tolerance management in cloud computing: A system-level perspective. Systems Journal, IEEE, 7(2), 288-297.
  21. Huth, A. , & Cebula, J. (2011). The Basics of Cloud Computing. United States Computer.
  22. Brian, O. , Brunschwiler, T. , Dill, H. , Christ, H. , Falsafi, B. , Fischer, M. , . . . & Zollinger, M. (2012). Cloud Computing. White Paper SATW.
  23. Youssef, A. E. (2012). Exploring Cloud Computing Services and Applications. Journal of Emerging Trends in Computing and Information Sciences, 3(6), 838-847.
  24. Xiong, N. , Vasilakos, A. V. , Yang, Y. R. , Qiao, C. , & Andy, Y. P. (2012). A class of practical self-tuning failure detection schemes for cloud communication networks. IEEE/ACM Transactions on Networking (ToN), submitted.
  25. Deng, J. , Huang, S. H. , Han, Y. S. , & Deng, J. H. (2010, December). Fault-tolerant and reliable computation in cloud computing. In GLOBECOM Workshops (GC Wkshps), 2010 IEEE (pp. 1601-1605). IEEE.
  26. 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.
  27. de Araújo Macêdo, R. , & e Lima, F. R. L. (2004). Improving the quality of service of failure detectors with SNMP and artificial neural networks. In Anais do 22o. Simpósio Brasileiro de Redes de Computadores (pp. 583-586)
  28. Sun, D. W. , Chang, G. R. , Gao, S. , Jin, L. Z. , & Wang, X. W. (2012). Modeling a dynamic data replication strategy to increase system availability in cloud computing environments. Journal of computer science and technology, 27(2), 256-272.
  29. Meshram, A. D. , Sambare, A. S. , & Zade, S. D. (2013). Fault Tolerance Model for Reliable Cloud Computing.
  30. Nguyen, H. , Shen, Z. , Tan, Y. , & Gu, X. (2013, July). FChain: Toward black-box online fault localization for cloud systems. In Distributed Computing Systems (ICDCS), 2013 IEEE 33rd International Conference on (pp. 21-30). IEEE.
  31. Joshi, S. C. , & Sivalingam, K. M. (2014). Fault tolerance mechanisms for virtual data center architectures. Photonic Network Communications, 28(2), 154-164.
  32. Wang, S. S. , Yan, K. Q. , & Wang, S. C. (2011). Achieving efficient agreement within a dual-failure cloud-computing environment. Expert Systems with Applications, 38(1), 906-915.
  33. Malik, S. , & Huet, F. (2011, July). Adaptive Fault Tolerance in Real Time Cloud Computing. In Services (SERVICES), 2011 IEEE World Congress on (pp. 280-287). IEEE.
  34. Bala, A. , & Chana, I. (2014). Intelligent failure prediction models for scientific workflows. Expert Systems with Applications.
  35. Chandra, T. D. , & Toueg, S. (1996). Unreliable failure detectors for reliable distributed systems. Journal of the ACM (JACM), 43(2), 225-267
Index Terms

Computer Science
Information Sciences

Keywords

Cloud Computing Fault Tolerance Failure Detector.

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