Abstract.In this contribution, the grid integration platform designed to simplify the development of web applications that make use of distributed computing (grid) is described. The core of this software consists of several modules that implement interaction with grid that implies authentication, data exchange and result visualization. Custom APIs are used to link application with distributed computing resources. The platform is specifically designed for numerical solution of large number of weakly-coupled simple tasks. This paper also describes an application that was built with this platform. Keywords: grid application, SOA, middleware, framework, time-spectral analysis, poly-frequency model PP. 84-95. REFERENCES 1. A.S. Tanenbaum and M. van Steen. Distributed Systems: Principles and Paradigms. Pearson Prentice Hall, 2007.
2. David P Anderson. Public computing: Reconnecting people to science. In Conference on Shared Knowledge and the Web, pages 17–19, 2003.
3. Ian Foster and Carl Kesselman. Globus: A metacomputing infrastructure toolkit. International Journal of High Performance Computing Applications, 11(2):115–128, 1997.
4. Jose Luis Vazquez-Poletti, Eduardo Huedo, Ruben S Montero, and Ignacio Martin Llorente. A comparison between two grid scheduling philosophies: EGEE WMS and GridWay. Multiagent and Grid Systems, 3(4):429–439, 2007.
5. Erwin Laure, A Edlund, F Pacini, P Buncic, S Beco, F Prelz, A Di Meglio, O Mulmo, M Barroso, Peter Z Kunszt, et al. Middleware for the next generation grid infrastructure. Technical report, CERN, 2004.
6. Ian Foster. Service-oriented science. Science, 308(5723):814–817, 2005.
7. Sukhoroslov O., Afanasiev A. Everest: A Cloud Platform for Computational Web Services. In Proceedings of the 4th International Conference on Cloud Computing and Services Science (CLOSER 2014). SCITEPRESS – Science and and Technology Publications, 2014, pp. 411-416.
8. Yu.A. Bychkov, G.A. Oparin, A.G. Feoktistov, V.G. Bogdanova, i A.S. Korsukov. Servis-orientirovannyy podkhod k organizatsii raspredelennykh vychisleniy s pomoshchyu instrumentalnogo kompleksa DISCENT. Informatsionnye tekhnologii i vychislitelnye sistemy, (2):7–15, 2014.
9. Grid execution management for legacy code architecture.
10. Apache Ignite. The Apache Foundation. URL:
http://ignite.incubator.apache.org
11. Univa Grid Engine. Univa Corporation. URL:
http://univa.com
12. I.M. Aleshin i K.I. Kholodkov. Primenenie raspredelennykh vychislitelnykh sistem k raschetu aposteriornykh raspredeleniy. Geofizicheskie issledovaniya, 15(4):73–80, 2014.
13. Walfredo Cirne, Daniel Paranhos, Lauro Costa, Elizeu Santos-neto, Francisco Brasileiro, Jacques Sauve, Campina Grande, Fabricio Alves, Barbosa Silva, Catolica Santos, Carla Osthoff Barros, Laboratorio Nacional, Computacao Cientifica, Cirano Silveira, and Hewlett Packard. Running bag-of-tasks applications on computational grids: The mygrid approach. In In ICPP, page 407, 2003.
14. Disco. Nokia Research Center URL: http://discoproject.org
15. John Deacon. Model-view-controller (mvc) architecture. Technical report, JDL, 2009.
16. AB MySQL. MySQL: the world’s most popular open source database. MySQL AB, 1995.
17. Josh Juneau. Object-relational mapping. In Java EE 7 Recipes, pages 369–408. Springer, 2013.
18. A.N. Zaytsev, V. I. Odintsov, V. V. Ivanov. Spektralnye osobennosti vostochnoy i zapadnoy elektrostruy v period magnitnoy buri 24 marta 1991 g. Geomagnetizm i aeronomiya, 39(1):35–41, 1991.
19. V.I. Odintsov, N. M. Rotanova, Yu. P. Tsvetkov, An Chenchang. Spektralnyy analiz anomalnogo magnitnogo polya zemli dlya raznovysotnykh semok. Geomagnetizm i aeronomiya, 40(2):59 – 66, 2000.
20. A Dmitriev, A. Belov, R Gorgutsa, V Ishkov, V. V. Kozlov, R Nymmik, V Odintsov, A Petrukovich, G Popov, E Romashets, et al. The development of the Russian space weather initiatives. Advances in Space Research, 31(4):855–860, 2003.
21. A.B. Barabanov. Identifikatsiya parametrov poligarmonicheskoy modeli rechevogo signala. Materialy XII Vserossiyskogo soveshchaniya po problemam upravleniya (VSPU-2014), S. 3038–3049, 2014.
22. A. A. Melnikov. Bystryy algoritm identifikatsii parametrov modeli golosovogo signala. Materialy XII Vserossiyskogo soveshchaniya po problemam upravleniya (VSPU-2014), s. 3090–3101, 2014.
23. David C Rife and Robert R Boorstyn. Multiple tone parameter estimation from discrete-time observations. Bell System Technical Journal, 55(9):1389–1410, 1976.
24. D.I. Yakushev. Geoinformatsionnoe modelirovanie prostranstvenno-vremennykh geofizicheskikh protsessov s poligarmonicheskoy strukturoy. Avtoreferat na soiskanie uchenoy stepeni doktora tekhnicheskikh nauk, 2008.
25. V.G. Getmanov. Algoritm razdeleniya blizkikh po chastote istochnikov vibratsii. Kolebaniya i vibratsionnaya aktivnost mashin i konstruktsiy, S. 157–160. Nauka, 1988.
26. V.G. Getmanov. Ob algoritme poiska po chastote v zadache otsenivaniya parametrov modeley poligarmonicheskikh signalov. Avtometriya, 45(3):83–89, 2009.
27. N.Ye. Timoshevskaya. O numeratsii perestanovok i sochetaniy dlya organizatsii parallelnykh vychisleniy v zadachakh proektirovaniya upravlyayushchikh sistem. Izvestiya Tomskogo politekhnicheskogo universiteta, 307(6):18–19, 2004.
28. Borzunov G.I. Getmanov, V. G. Algoritm parallelnykh vychisleniy dlya zadachi spektralno - vremennogo analiza na bazisnykh poligarmonicheskikh funktsiyakh. Informatsionnye tekhnologii, 21(9), 2015.
29. K.I. Kholodkov, I.M. Aleshin, V.N. Koryagin, O. V. Sukhoroslov, A.N. Shogin. Opyt razvertyvaniya gridinfrastruktury dlya podderzhki vychislitelnykh veb-servisov. Nauchno-tekhnicheskaya informatsiya. Seriya 1, (4):15–19, 2012.
30. A.P. Prudnikov, Yu.A. Bychkov, and O.I. Marichev. Integraly i ryady: Elementarnye funktsii, t. 1. "Nauka", M.: 1981.
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