زمانبندی کاربردهای جریان کاری علمی در محیط چندابری با استفاده از الگوریتم جستجوی فاخته
محورهای موضوعی : مهندسی برق و کامپیوترسمیه محمدی 1 * , لطیف پورکریمی 2 , سمیه عبدی 3
1 - دانشگاه آزاد اسلامی واحد کرمانشاه
2 - دانشگاه رازی
3 - دانشگاه آزاد اسلامی واحد اسلام آباد غرب
کلید واژه: چندابریزمانبندیجریان کاری علمی بهینهسازی هزینهالگوریتم جستجوی فاخته,
چکیده مقاله :
محیطهای چندابری شامل منابع متنوع قابل ملاحظهای هستند که هزینههای زمانبندی کاربردهای جریان کاری در چنین محیطهایی میتواند به طور چشمگیری کاهش یابد و همچنین محدودیت ارائه منابع توسط فراهمکنندگان تجاری ابر رفع شود. بر این اساس، این تحقیق به مسأله زمانبندی کاربردهای جریان کاری علمی در محیط چندابری تحت قید مهلت زمانی با هدف کمینهسازی هزینه میپردازد. در اين مقاله با به كارگيري الگوريتم جستجوي فاخته که يكي از مشهورترین روشهاي جستجوي فراابتكاري میباشد، الگوريتمي براي مسأله زمانبندی کاربردهای جریان کاری در محیط چندابری ارائه شده است. الگوريتم فراابتكاري جستجوي فاخته قادر است در مدت زماني كوتاه فضاي جواب را جستجو نموده و جوابهايي را در همسايگي جواب بهینه سراسری بيابد كه به آن نزديك ميباشد. نتایج به دست آمده نشان میدهند که راهکار پیشنهادی این تحقیق در مقایسه با دیگر راهکارهای فراابتکاری در موارد کاهش هزینه کارایی بهتری داشته و همچنین جوابهاي به دست آمده از الگوريتم فراابتکاری پیشنهادي، در حد مطلوبی نزديک به جوابهاي بهینه سراسری به دست آمده از مدل رياضی است.
Multi-cloud environments consist of the considerable variety of resources where the cost of scheduling workflow applications can be significantly reduced in such environments and the resource limitationsimposed by commercial cloud providers can bealso overcome. Accordingly, this study addresses the scheduling of scientific workflowapplications in a multi-cloud environment under a deadline with the aim of minimizing costs. In this paper,an algorithm for scheduling of workflow applications in multi-cloud environment is presented using the cuckoo search algorithm which is one of the most popular meta-heuristic methods. The Cuckoo Search Algorithm is able to search the solution space in a short time and find solutions in the vicinity of the optimal global solution that is close to it. The results show that the proposed approach of this research has better performance in comparison with other meta- heuristic approach in terms of cost reduction. Moreover, the obtained solutions of the proposed meta- heuristic algorithm are in a desirable degree close to the global optimal solutions of mathematical model.
[1] M. Mattoso, C. Werner, G. H. Travassos, V. Braganholo, E. Ogasawara, D. Oliveira, S. Cruz, W. Martinho, and L. Murta, "Towards supporting the life cycle of large scale scientific experiments," Int. J. Bus. Process Integr. Manag., vol. 5, no. 1, pp. 79-92, May 2010.
[2] T. Hey, S. Tansley, and K. M. Tolle, The Fourth Paradigm: Data-Intensive Scientific Discovery, vol. 1. Microsoft Research Redmond, WA, 2009.
[3] I. J. Taylor, E. Deelman, D. B. Gannon, and M. Shields, Workflows for E-Science: Scientific Workflows for Grids, Springer Publishing Company, Incorporated, 2014.
[4] L. Grandinetti, High Performance Computing and Grids in Action, vol. 16, IOS Press, 2008.
[5] L. M. Vaquero, L. Rodero-Merino, J. Caceres, and M. Lindner, "A break in the clouds: towards a cloud definition," ACM SIGCOMM Comput. Commun. Rev., vol. 39, no. 1, pp. 50-55, Dec. 2008.
[6] I. Foster, Y. Zhao, I. Raicu, and S. Lu, "Cloud computing and grid computing 360-degree compared," in Proc. Grid Computing Environments Workshop, 10 pp., Austin, TX, USA , 12-16 Nov. 2008.
[7] F. Wu, Q. Wu, and Y. Tan, "Workflow scheduling in cloud: a survey," J. Supercomput., vol. 71, no. 9, pp. 3373-3418, May 2015.
[8] S. Abrishami, M. Naghibzadeh, and D. H. J. Epema, "Deadline-constrained workflow scheduling algorithms for infrastructure as a service clouds," Futur. Gener. Comput. Syst., vol. 29, no. 1, pp. 158-169, Jun. 2013.
[9] S. Abrishami, M. Naghibzadeh, and D. H. J. Epema, "Cost-driven scheduling of grid workflows using partial critical paths," IEEE Trans. Parallel Distrib. Syst., vol. 23, no. 8, pp. 1400-1414, Aug. 2012.
[10] B. Lin, W. Guo, G. Chen, N. Xiong, and R. Li, "Cost-driven scheduling for deadline-constrained workflow on multi-clouds," in Proc. IEEE Int. Parallel and Distributed Processing Symp. Workshop, IPDPSW’15 , pp. 1191-1198, Hyderabad, India, 25-29 May 2015.
[11] B. Lin, et al., "A pretreatment workflow scheduling approach for big data applications in multi cloud environments," IEEE Trans. on Network and Service Management, vol. 13, no. 3, pp. 581-594, Sept. 2016.
[12] H. M. Fard, R. Prodan, and T. Fahringer, "A truthful dynamic workflow scheduling mechanism for commercial multicloud environments," IEEE Trans. Parallel Distrib. Syst., vol. 24, no. 6, pp. 1203-1212, Jun. 2013.
[13] S. Mohammadi, H. Pedram, and L. PourKarimi, "Integer linear programming-based cost optimization for scheduling scientific workflows in multi-cloud environments," the J. of Supercomputing, vol. 74, no. 9, pp. 4717-4745, Sep. 2018.
[14] M. S. Hosseini Shirvani, "A hybrid meta-heuristic algorithm for scientific workflow scheduling in heterogeneous distributed computing systems," Engineering Applications of Artificial Intelligence, vol. 90, Article No.: 103501, 20 pp., Apr. 2020.
[15] K. R. Escott, H. Ma, and G. Chen, "Genetic programming based hyper heuristic approach for dynamic workflow scheduling in the cloud," in Proc. Int. Conf. on Database and Expert Systems Applications, pp. 3141-3148, Canberra, ACT, Australia, 1-4 Dec. 2020.
[16] N. Rizvi and D. Ramesh, "HBDCWS: heuristic-based budget and deadline constrained workflow scheduling approach for heterogeneous clouds," Soft Computing, vol. 24, pp. 18971-18990, Jul. 2020.
[17] G. B. Berriman, et al., "Montage: a grid-enabled engine for delivering custom science-grade mosaics on demand," SPIE Astronomical Telescopes+ Instrumentation, pp. 221-232, Sept. 2004.
[18] P. Maechling, et al., "SCEC cybershake workflows-automating probabilistic seismic hazard analysis calculations," in Workflows for E-Science: Scientific Workflows for Grids, I. J. Taylor, E. Deelman, , D. B. Gannon, and M. Shields, (Eds.), pp. 143-163, Springer, 2007.
[19] -, USC Epigenome Center, [Online]. Available: http://epigenome.usc.edu.
[20] "LIGO project, LIGO-laser interferometer gravitational wave observatory," [Online]. Available: http://www.ligo.caltech.edu/.
[21] X. S. Yang and S. Deb, "Cuckoo search via Levy flights," in Proc. World Congress on,Nature & Biologically Inspired Computing, NaBIC’09, pp. 210-214, Coimbatore, India, 91-11 Dec. 2009.