A Bio-Informatics Model for Task assignment and Fault Removal in Cloud Architecture

Authors

  • Umesh Dwivedi Ph.D. Scholar, Dr. A.P.J. Abdul Kalam Technical University, Lucknow,Uttar Pradesh, India. Author
  • Dr. Harsh Dev Professor and Dean in Research Wing, Pranveer Singh Institute of Technology, Kanpur Author

DOI:

https://doi.org/10.61841/ydmx1e71

Keywords:

cloud computing, , fault tolerance, FASTA, BLAST, VM, Resources

Abstract

 

Cloud computing is an emerging field and currently is being used in almost all the economical and manufacturing fields. Main reason of attraction towards this field is its number of attractive and beneficial features. Cloud architecture is designed in a fashion, that it can execute the tasks provided by the client in minimum time, minimum cost and without any fault. These assigned tasks need some resources for their execution. These resources are to be provided by the data centrers with help of virtual machines available there. Proper assignment of virtual machines to each task is very difficult. If this is not done properly, there is huge wastage of resources. Number of tasks are left unexecuted just because they are not getting their required resources or they have to wait for much longer time. Even if virtual machines get assigned to the tasks, there is no guarantee of proper resource assignment. Either resources are provided in bulk or there is a scarcity of resources for the task. It is also an arduous process. This paper uses two biotechnology algorithms named FASTA and BLAST for handling this proper resource assignment problem. These algorithms work in biological field for DNA mapping. They promptly map the complete strip in parallel. This paper uses these biological algorithms for resource assignments for the tasks to be executed. This paper explains about these biological algorithms and how they are nifty in resource assignment problem and its solution in very less amount of time. Finally, error occurring conditions which may arise while approximation adoption of result are explained and solved in detail.

 

 

 

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References

[1] Sun Microsystems, Inc. “Introduction to Cloud Computing Architecture” White Paper 1st Edition, June 2009

[2] Swati Pawar, Jayoti Vidyapeeth, “A Survey on Fault Tolerance and its Techniques in Cloud Computing”, International Journal of Engineering Technology and Computer Research (IJETCR),

Volume 3; Issue 3; May-June 2015; Page No. 116-120, Available Online at www.ijetcr.org

[3] AnjuBala, Inderveer Chana,” Fault Tolerance◻Challenges, Techniques and Implementation in Cloud Computing” IJCSI International Journal of Computer Science Issues, Vol. 9, Issue 1, No 1, January 2012 ISSN (Online): 1694-0814 www.IJCSI.org

[4] Y.M. Teo, B.L. Luong, Y. Song, T. Nam, ”Cost◻Performance of Fault Tolerance in Cloud Computing, International Conference on Advanced Computing and Applications, (Special Issue of Journal of Science and Technology, Vol. 49(4A), pp. 61-73), Ho Chi Minh, Vietnam, October 19-21, 2011.

[5] Ravpreet Kaur, Manish Mahajan , “Fault Tolerance in Cloud Computing”, International journal of Science Technology & Management (IJSTM) ISSN: 2229-6646 Presented in National Conference on RTICCN-2015 at CGC-COE , Landran , Mohali(Punjab) on 26-27th March 2015.

[6] Jhawar, Ravi, Vincenzo Piuri, and Marco Santambrogio., "Fault tolerance management in cloud computing: A system-level perspective." Systems Journal, IEEE 7.2 (2013): 288-297.

[7] Scot E Dowd, Joaquin Zaragoza, Javier R Rodriguez,, Melvin J Oliver, Paxton R Payton, “Windows .NET Network Distributed Basic Local Alignment Search Toolkit (W.ND-BLAST)”, BMC Bioinformatics 2005, 6:93,Pg 1-14.

[8] Altschul S, Gish W, Miller W, Myers E, Lipman DJ, Basic Local Alignment Search Tool. Journal of Molecular Biology 1990,215:403-410.

[9] Altschul SF, Madden TL, Schaffer AA, Zhang J, Zhang Z, Miller W, Lipman DJ, “ Gapped BLAST and PSI-BLAST: A new generation of protein database search programs. Nucleic Acids Res 1997, 25:3389-402.

[10] R. Bjornson, A. Sherman, S. Weston, N. Willard and J. Wing. Turboblast, “A parallel implementation of blast based on the turbohub process integration architecture”, IPDPS 2002 Workshops, April 2002.

[11] R. Braun, K. Pedretti, T. Casavant, T. Scheetz, C. Birkett, and C. Roberts, “Parallelization of local BLAST service on workstation clusters”, Future Generation Computer Systems 17(6)},745-754, April 2001

[12] .J. D. Grant, R. L. Dunbrack, F. J. Manion and M. F. Ochs,”BeoBLAST: distributed BLAST and PSI-BLAST on a Beowulf cluster”, Bioinformatics, 18(5)}:765-766, 2002.

[13] M. Dumontier, and Christopher WV Hogue , NBLAST: a cluster variant of BLAST for NxN comparisons”, BMC Bioinformatics, 3:13, 2002,

[14] Alejandro A. Schaffer, Yuri I. Wolf, Chris P. Ponting, Eugene V. Koonin, L. Aravind, Stephen F.Altschul, “IMPALA: matching a protein sequence against a collection of PSI-BLAST-constructed position-specific score matrices”, National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD 20894, USA and Department of Biology, Texas A&M University, Biological Sciences Building West, College Station, TX 77843, USA Received on March 19, 1999 ; revised on July 28, 1999; accepted on August 4, 1999, Vol 15.

[15] D. J. Sorin, "Fault Tolerant Computer Architecture," Synthesis Lectures on Computer Architecture, vol. 4, no. 1, p. 2, 2009.

[16] A. Avizienis, J. C. Laprie, B. Randell and C. Landwehr, "Basic concepts and taxonomy of dependable and secure computing," Dependable and Secure Computing, IEEE Transactions on, vol. 1, no. 1, pp. 11-33, 2004.

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Published

31.10.2020

How to Cite

Dwivedi, U., & Dev, H. (2020). A Bio-Informatics Model for Task assignment and Fault Removal in Cloud Architecture. International Journal of Psychosocial Rehabilitation, 24(8), 8271-8282. https://doi.org/10.61841/ydmx1e71