Study of Various Reactive Fault Tolerance Techniques in Cloud Computing

Authors

  • Kumar A CS and IT, Central University of Jammu, Samba, India
  • Malhotra D CS and IT, Central University of Jammu, Samba, India

Keywords:

Reactive Fault Tolerance, Cloud Computing

Abstract

Cloud is large, complex and distributed in nature. It has many features like availability, Reliability and performance of the cloud. Due to its large size and complex nature it is prone to various types of fault and failure like data unavailable, data deletion or corruption etc. Cloud are made as fault tolerant system that tolerate any imminent fault or failure, but still sometime fault happens that disrupts the normal service of cloud. Many researchers gave different technique like replication, checkpointing , Retry ,resubmission etc. to tolerate the failure. In this paper, study of various reactive fault tolerance techniques has been done and after analysis conclusion is presented with some future scope. Keywords: Replication, Checkpointing, Resubmission, Reliability

References

S. Prathiba and S. Sowvarnica, “Survey of failures and fault tolerance in cloud,” in 2017 2nd International Conference on Computing and Communications

Technologies (ICCCT), 2017, pp. 169–172.

G. R. Kalanirnika and V. M. Sivagami, “Fault

Tolerance in Cloud Using Reactive and Proactive Techniques,” Int. J. Comput. Sci. Eng. Commun., vol. 3, no. 3, pp. 1159–1164, 2015.

S. Kadekodi, “A Compression in Checkpointing and Fault Tolerance Systems,” ACM Ref. Format Saurabh Kadekodi ACM Trans. Em-bedd. Comput. Syst. V, N,

Artic. A, vol. 8, 2013.

A. Rajalakshmi, D. Vijayakumar, and K. G.

Srinivasagan, “An improved dynamic data replica selection and placement in cloud,” 2014 Int. Conf.

Recent Trends Inf. Technol. ICRTIT 2014, vol. 3, no. 3, 2014.

A. M. Saleh and J. H. Patel, “Transient-Fault Analysis for Retry Techniques,” IEEE Trans. Reliab., vol. 37, no. 3, pp. 323–330, 1988.

Y. Kwon, M. Balazinska, and A. Greenberg, “Fault-tolerant

Stream Processing using a Distributed,

Replicated File System.”

T. Nadu, “Fault tolerant workflow scheduling based on replication and resubmission of tasks in Cloud Computing,” Int. J. Comput. Sci. Eng., vol. 4, no. 6, pp. 996–1006, 2012.

L. M. M. Visuwasam, “Checkpoint-based Intelligent Fault tolerance For Cloud Service Providers,” no. 2, pp. 59–64, 2012.

Q. Wei, B. Veeravalli, B. Gong, L. Zeng, and D. Feng,

“CDRM: A Cost-Effective Dynamic Replication Management

Scheme for Cloud Storage

Cluster,” in 2010 IEEE International Conference on Cluster Computing, 2010, pp. 188–196.

G. Yao, Y. Ding, and K. Hao, “Using Imbalance CharacteristicforFault-TolerantWorkflow

Scheduling in Cloud Systems,” IEEE Trans. Parallel Distrib. Syst., vol. 28, no. 12, pp. 3671–3683, Dec. 2017.

E. AbdElfattah, M. Elkawkagy, and A. El-Sisi, “A reactive fault tolerance approach for cloud computing,” in 2017 13th International Computer Engineering Conference (ICENCO), 2017, pp. 190– 194.

M. K. Gokhroo, M. C. Govil, and E. S. Pilli,“Detecting and mitigating faults in cloud computing environment,” 3rd IEEE Int. Conf. , 2017.

V. B. Souza, X. Masip-Bruin, E. Marin-Tordera, W.Ramirez, and S. Sanchez-Lopez, “Proactive vs reactive failure recovery assessment in combined Fog-to-Cloud (F2C) systems,” in 2017 IEEE 22nd International Workshop on Computer Aided Modeling and Design of Communication Links and Networks (CAMAD), 2017, pp. 1–5.

P. Padmakumari, A. Umamakeswari, and M.Akshaya, “Hybrid Fault Tolerant Scheme to Manage VM Failure in the

Cloud,” Indian J. Sci. Technol. ISSN, no. 948, pp. 974–6846, 2016.

O. Subasi, G. Yalcin, F. Zyulkyarov, O. Unsal, and J.Labarta, “Designing and Modelling Selective Replication for FaultTolerant HPC Applications,” Proc. - 2017 17th IEEE/ACM

Int. Symp. Clust. Cloud Grid Comput. CCGRID 2017, pp. 452–457, 2017.

Downloads

Published

2025-11-13

How to Cite

[1]
A. Kumar and D. Malhotra, “Study of Various Reactive Fault Tolerance Techniques in Cloud Computing”, Int. J. Comp. Sci. Eng., vol. 6, no. 5, pp. 54–60, Nov. 2025.