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Vol: 61(75) No: 1 / March 2016 Supporting Health Smart System Applications in Scientific Gateway Environment Krisztian Karoczkai MTA SZTAKI, H-1518 Budapest, Pf. 63., Hungary, phone: +36 (1) 666-5554, e-mail: krisztian.karoczkai@sztaki.hu Miklos Kozlovszky Óbuda University, John von Neumann Faculty of Informatics, Biotech Lab, Bécsi str. 96/b., H-1034, Budapest, Hungary, phone: +36 (1) 666-5554, e-mail: miklos.kozlovszky@uni-obuda.hu Peter Kacsuk MTA SZTAKI, H-1518 Budapest, Pf. 63., Hungary, phone: +36 (1) 666-5554, e-mail: kacsuk@sztaki.hu Keywords: smart system application, execution optimization, execution time minimization, direct cloud Abstract Smart system applications are spreading widely good example of such is health monitoring. Data captured from sensors arrive continuously and only efficient large scale data handling using data stream processing can cope with the transport requirements. Stream processing means that without intermediate storage the data should be processed as they are received from the sensors. Storing and transporting data takes a lot of time, and data transport time has significant impact on the overall execution of the health monitoring smart application. In this paper on one hand we have defined an execution model for smart system applications for common science gateway solutions with minimized data movement on the other hand we have developed a simulation environment and we have investigated the influencing factors of the time needed to execute the jobs. Our ultimate goal is to optimize the overall time needed to process data and submit the smart system applications. With help of statistical tools we have also performed computations and in case of different middlewares and storages we have carried out measurements. The results show that both the job submission time and the data transmission/delivery time is minimal for applications that use Direct Cloud access in Pgrade/gUSE/DCI-Bridge environment. We have also investigated the effects of the parallelization degree on the system efficiency and the results show that until a certain degree the parallelization also positively effects the system’s throughput. References [1] P. Kacsuk: P-GRADE portal family for Grid infrastructures, Concurrency and Computation: Practice and Experience Journal, vol. 23, no. 3, pp. 235-245, 2012. [2] Peter Kacsuk, Zoltan Farkas, Miklos Kozlovszky, Gabor Hermann, Akos Balasko, Krisztian Karoczkai and Istvan Marton: WS-PGRADE/gUSE Generic DCI Gateway Framework for a Large Variety of User Communities, Journal of Grid Computing, vol. 9, no. 4, pp 479-499, 2012. [3] Tamas Kiss, Pamela Greenwell, Hans Heindl, Gabor Terstyanszky and Noam Weingarten, Parameter Sweep Workflows for Modelling Carbohydrate Recognition, Journal of Grid Computing, vol. 8, no. 4, pp. 587-601, 2010. [4] Kozlovszky M, Karoczkai K, Marton I, Balasko A, Marosi A, Kacsuk P: Enabling generic distributed computing infrastructure compatibility for workflow management systems, Computer Science Journal, vol. 13, no. 3, pp. 61-78, 2012. [5] P Kacsuk, Z. Farkas, M. Kozlovszky, G. Hermann, A. Balasko, K Karoczkai, I Marton: WS-PGRADE/gUSE Generic DCI Gateway Framework for a Large Variety of User Communities, Journal of Grid Computing, vol. 10, no. 4, pp. 601-630, 2012. [6] Michael Stonebraker, U. Çetintemel, Stan Zdonik: The 8 requirements of real-time stream processing, ACM SIGMOD, vol. 34, no. 4, pp. 42-47, Dec. 2005. [7] Don Carney, U. Çetintemel, Mitch Cherniack, Christian Convey, Sangdon Lee, Greg Seidman, Michael Stonebraker, Nesime Tatbul, Stan Zdonik: Monitoring streams: a new class of data management applications, Proceedings of 28th International Conference on Very Large Data Bases (VLDB \'02), pp. 215-226, 2002. [8] Amin Zahedi-Khameneha, Raimar J. Scherera, Mehdi Zaréb: A non-parametric wave type based model for real-time prediction of strong ground motion accelerogram, Soil Dynamics and Earthquake Engineering, vol. 49, pp. 181-196, June 2013. [9] Branzanti, M.; Colosimo, G.; Crespi, M. ; Mazzoni, A. :GPS Near-Real-Time Coseismic Displacements for the Great Tohoku-oki Earthquake, Geoscience and Remote Sensing Letters, IEEE March 2013, pp. 372-376, DOI: 10.1109/LGRS.2012.2207704. [10] Jianghui Geng, Yehuda Bock, Diego, Melgar, Brendan W. Crowell, Jennifer S. Haase, Cecil H., Ida M: A new seismogeodetic approach applied to GPS and accelerometer observations of the 2012 Brawley seismic swarm: Implications for earthquake early warning, DOI: 10.1002/ggge.20144J. [11] Eva Sciacca, Marilena Bandieramonte, Ugo Becciani, Alessandro Costa, Mel Krokos, Pietro Massimino, Catia Petta, Costantino Pistagna, Simone Riggi and Fabio Vitello, VisIVO Science Gateway: a Collaborative Environment for the Astrophysics Community, Proceedings of 5th International Workshop on Science Gateways. Zurich, Switzerland, 3-5 June, 2013. [12] Eva Sciacca, Marilena Bandieramonte, Ugo Becciani, Alessandro Costa, Mel Krokos, Pietro Massimino, Catia Petta, Costantino Pistagna, Simone Riggi and Fabio Vitello, VisIVO Workflow-Oriented Science Gateway for Astrophysical Visualization, Proceedings of 21st Euromicro International Conference on Parallel, Distributed and Network-Based Processing (PDP), 2013 Processing (PDP). [13] http://www.lpds.sztaki.hu/node/192 [acc.09.09.2013] [14] Hajnal, Ákos, Zoltán Farkas, and Péter Kacsuk: Data avenue: remote storage resource management in WS-PGRADE/gUSE, Proceedings of 2014 6th International Workshop on Science Gateways (IWSG 2014). [15] Farkas, Zoltán, Hajnal, Ákos, Kacsuk, Péter: WS-PGRADE/gUSE and Clouds, in: Science Gateways for Distributed Computing Infrastructures, Springer, Cham, pp. 97-109, DOI: 10.1007/978-3-319-11268-8_7. |