Optimization of Cost and Meeting Deadline in Scientific Workflow

  IJETT-book-cover  International Journal of Engineering Trends and Technology (IJETT)          
  
© 2017 by IJETT Journal
Volume-48 Number-4
Year of Publication : 2017
Authors : Ruchita P. Pingale, Smita S. Patel
DOI :  10.14445/22315381/IJETT-V48P239

Citation 

Ruchita P. Pingale, Smita S. Patel "Optimization of Cost and Meeting Deadline in Scientific Workflow", International Journal of Engineering Trends and Technology (IJETT), V48(4),219-223 June 2017. ISSN:2231-5381. www.ijettjournal.org. published by seventh sense research group

Abstract
Cloud computing is booming technology in the area of information technology. Nowadays, the clouds are known as the global storage and used by many companies, schools, websites etc. The elasticity property of the cloud makes it a suitable platform for the execution of the scientific workflow with the deadline constraint. Resource required for the application is dynamically allocated. The existing algorithms in the area of the scientific workflow either try to minimize the cost or focus on minimizing execution time while trying to meet the application deadline. Also, the existing algorithm considers only one data Centre of the cloud. To increase the performance of scheduling process within the deadline we proposed the enhancement to the EIPR algorithm which uses the idle time slots for providing resource and the budget surplus to replicate the task. Replication uses another data Centre for scheduling process. However, the soft deadline is considered for the process. The working of EIPR algorithm checked on the experiments like montage (25, 50- this is the no of task included in the graph). This shows the implemented algorithm (EIPR) is able to minimize the cost and the execution time of scheduling process in scientific workflow.

 References

[1] Rodrigo N. Calheiros, RajkumarBuyya, "Meeting Deadlines of Scientific Workflows inPublic Clouds with Tasks Replication"SYSTEMS, VOL. 25,pp-1787-1796 , JULY 2014.J. Breckling, Ed., The Analysis of Directional Time Series: Applications to Wind Speed and Direction, ser. Lecture Notes in Statistics. Berlin, Germany: Springer, 1989, vol. 61.
[2] S.Abrishami, M. Naghibzadeh, and D. Epema, ‘‘Deadline- Constrained Workflow Scheduling Algorithms for IaaSClouds,’’FutureGener. Comput. Syst., vol. 29, no. 1, pp. 158-169, Jan. 2013.
[3] Ms.K.Sathya, Dr.S.Rajalakshmi,"Deadline Based Task Scheduling in Cloud with Effective Provisioning Cost using LBMMC Algorithm",Volume 1 Issue 7, November 2014.
[4] Xin YE,JiweiLIANG,SihaoLIU,Jia LI,"A Survey on Scheduling Workflows in Cloud Environment",International Conference on Network and Information Systems for Computers, pp.344-348, November 2015. (2002) The IEEE website. [Online]. Available: http://www.ieee.org/
[5] Ms. B. Poornima,Prof. S. R. Mugunthan,"Meeting Deadlines Constraint of Scientific Workflows in Multiple Cloud by Using Task Replication",(ICSNS -2015), Feb. 25 – 27, 2015.FLEXChip Signal Processor (MC68175/D), Motorola, 1996.
[6] S. Abrishami, M. Naghibzadeh,"Deadline-constrained workflow scheduling in software as a service Cloud",FutureGener. Comput. Syst., vol.19, 680–689, Nov.2012.
[7] G. Juve, A. Chervenak, E. Deelman, S. Bharathi, G. Mehta, and K. Vahi, “Characterizing and Profiling Scientific Workflows,’’ Future Gener.Comput.Syst., vol. 29, no. 3, pp. 682-692, Mar. 2013.
[8] Nallakumar. R1, SruthiPriya. K. S2 ”A Survey on Deadline Constrained Workflow Scheduling Algorithms in CloudEnvironment” (IJCST) – Volume 2 Issue 5, Sep-Oct 2014,pp 44-50.
[9] Eun-KyuByun, Yang-Suk Kee, Jin-Soo Kim, SeungryoulMaeng,"Cost optimized provisioning of elastic resources for application workflows",Future Generation Computer Systems 27 pp. 1011–1026,may 2011.
[10] KassianPlankensteiner,RaduProdan,"Meeting Soft Deadlines in Scientific workflows Using Resubmission Impact",PARALLEL AND DISTRIBUTE SYSTEMS, VOL. 23, NO. 5, MAY 2012.

Keywords
Scientific Workflow, Soft Deadline, EIPR, Data Centre.