Hybrid Service for Business Contingency Plan and Recovery Service as a Disaster Recovery Framework for Cloud Computing

Fatemeh Sabbaghi, Arash Mahboubi, Siti Hajar Othman

Abstract


Cloud computing is the latest effort in delivering computing resources as a service to small and medium sized enterprises. These enterprise organizations require installing and maintaining expensive equipment to keep business up and running at all the times. Naturally this requires building an infrastructure flexible enough to respond to any threat under all circumstances. Any disaster may be considered to be a threat associated with the IT infrastructure in a data center. Disaster can occur either naturally or by humans. This paper is focused on how disaster may be controlled in a cloud computing data center which provides services to an organization and how to keep the organization business running while a disaster strikes. The availability and performance of any service is measured by its overall uptime. Recent recovery techniques that have been developed in cloud computing domain have several advantages and disadvantages. Therefore, researchers should conduct some investigations in this field. A hybrid service which utilize redundancy and fault tolerance techniques for providing more accurate recovery in cloud computing when disaster strikes is proposed in order to overcome these challenges in this paper. This hybrid service integrates the Infrastructure as a Service (IaaS) and Disaster Recovery as another Service (DRaaS). The proposed framework is formed by the integration of five essential types of proven redundancy techniques that have a major impact on the uptime of the services during disaster in cloud data centers. For evaluation of the proposed framework, a survey was conducted through a questionnaire presented to and filled by networking professionals and experts. The outcome of data analysis indicates that redundancy-based disaster recovery framework improves the performance of data center recovery and results in a high level of availability of the restored enterprise when disaster strikes. A total of 59.4 % of survey respondents accepted the fact that this framework reduces more than 70 % of threats associated with disaster.


Keywords


Cloud computing, Disaster recovery, Infrastructure as a Service (IaaS), Disaster Recovery as a Service (DRaaS)

Full Text:

Abstract PDF

References


Alhazmi, O. H. and Malaiya, Y. K. (2013). Evaluating disaster recovery plans using the cloud. Proceedings-Annual of Reliability and Maintainability Symposium (RAMS), IEEE.

Bhardwaj, S., Jain, L. and Jain, S. (2010). Cloud computing: A study of infrastructure as a service (IAAS). International Journal of engineering and information Technology, 2(1): 60-63.

Bocci, M., Cowburn, I. and Guillet, J. (2008). Network high availability for ethernet services using

IP/MPLS networks. Communications Magazine, IEEE, 46 (3), 90-96.

Bohm, M., Leimeister, S., Riedl C. and Krcmar, H. (2010). Cloud computing and computing evolution. Technische Universität München (TUM), Germany, CRC press.

Cegiela, R. (2006). Selecting technology for disaster recovery. International Conference on Dependability of Computer Systems. DepCos-RELCOMEX'06, IEEE, 160-167.

Cegiela, R. (2006). Selecting technology for disaster recovery. Dependability of Computer Systems, 2006. DepCos-RELCOMEX'06. International Conference on Dependability of Computer Systems, IEEE, 160-167.

Engelmann, C., Scott, S. L., Leangsuksun, C. and He, X. (2006). Active/active replication for highly available HPC system services. Journal of Computers, 1(8), 43-54.

García-Peñalvo, F. J., Johnson, M., Alves, G. R., Minović, M. and Conde-González, M. Á. (2014). Informal learning recognition through a cloud ecosystem. Future Generation Computer Systems. 32, 282-294.

George, D. and Mallery, P. (2010). SPSS for Windows Step by Step: A Simple Guide and Reference. 18.0 Update: Pearson Education, Inc.

Girola, M., Friedman, M., Lewis, M. and Tarenzio, A. M. (2011). IBM Data Center Networking: Planning for virtualization and cloud computing. IBM Redbooks.

Hsu, I. P.-S., Jalan R., Kamat G., Kuo A. T.-C. and Moncada-Elias, J. (2009). System and method for providing network route redundancy across layer 2 devices, Google Patents.

Jian-hua, Z. and Nan, Z. (2011). Cloud Computing-based Data Storage and Disaster Recovery. International Conference on Future Computer Science and Education (ICFCSE), IEEE, 629-632.

Lin, G., Zhi-hai, Y., Hai-bo, L., Le-jun, Z. and Jian-pei, Z. (2010). A remote data disaster recovery system model based on undo. Sixth International Conference on Networked Computing and Advanced Information Management (NCM), IEEE, 123-128.

Luetkehoelter, J. (2008). Disaster Recovery Planning, Pro SQL Server Disaster Recovery, publisher: Apress, ISBN 978-1-4302-0601-9, 269-291.

Lufaj, B. (2012). Virtual Desktop and Cloud Services: New Security Demand. Master's thesis of Gjøvik University College.

Mell, P. and Grance, T. (2011). The NIST definition of cloud computing. National Institute of Standards and Technology Special Publication. 800-145.

Pirro, G., Trunfio, P., Talia, D., Missier, P. and Goble, C. (2010). Ergot: A semantic-based system for service discovery in distributed infrastructures. 10th International Conference on Cluster, Cloud and Grid Computing (CCGrid), IEEE/ACM, 263-272.

Prakash, S., Mody, S., Wahab, A., Swaminathan, S. and Paramount, R. (2012). Disaster recovery services in the cloud for SMEs. International Conference on Cloud Computing Technologies, Applications and Management (ICCCTAM), IEEE. 139-144.

Reh, R., Mursidi, M. L. and Husin, N. A. A. (2011). Reliability analysis for pilot survey in integrated survey management system. 5th Malaysian Conference in Software Engineering (MySEC), IEEE. 220-222.

Sharma, K. and Singh, K. R. (2012). Online Data Back-up and Disaster Recovery Techniques in Cloud Computing: A Review. International Journal of Engineering and Innovative Technology (IJEIT) 2(5): 249-254.

Song, C.-w., Park S., Kim, D.-w. and Kang, S. (2011). Parity Cloud Service: A Privacy-Protected Personal Data Recovery Service. 10th International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom), IEEE, 812-817.

Sriram, I. and Khajeh-Hosseini, A. (2010). Research agenda in cloud technologies. arXiv preprint arXiv: 1001.3259.

Sun, L., An, J., Yang, Y. and Zeng M. (2011). Recovery strategies for service composition in dynamic network. International Conference on Cloud and Service Computing (CSC), IEEE. 60-64.

Suganya , S. D. (2015). Evaluation of disaster recovery in cloud computing. International Journal of Multidisciplinary Research and Development 2(6): 300-304.

Susanto, H., Almunawar, M. N. and Kang, C. C. (2012). Toward Cloud Computing Evolution. arXiv preprint arXiv: 1209.6125.

Manvi Mishra, I. A., Singh, P., and Prabhakar, S. (2014). An assessment of cloud computing: evolution. International Journal of Research in Engineering and Technology (IJRET). 668-674.

Ueno, Y., Miyaho, N. and Suzuki, S. (2009). Disaster recovery mechanism using widely distributed networking and secure metadata handling technology. Proceedings of the 4th edition of the UPGRADE-CN workshop on Use of P2P, GRID and agents for the development of content networks, ACM. 45-48.

Ueno, Y., Miyaho, N., Suzuki, S. and Ichihara, K. (2010). Performance Evaluation of a Disaster Recovery System and Practical Network System Applications. Fifth International Conference on Systems and Networks Communications (ICSNC), IEEE, 195-200.


Refbacks

  • There are currently no refbacks.


Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.