Integrating Grid Computing Technology into Multimedia Application

  IJCTT-book-cover
 
International Journal of Computer Trends and Technology (IJCTT)          
 
© 2015 by IJCTT Journal
Volume-23 Number-3
Year of Publication : 2015
Authors : Rafid Al-Khannak, Abdulkareem A. Kadhim, Nada S. Ibrahim
  10.14445/22312803/IJCTT-V23P122

MLA

Rafid Al-Khannak, Abdulkareem A. Kadhim, Nada S. Ibrahim "Integrating Grid Computing Technology into Multimedia Application". International Journal of Computer Trends and Technology (IJCTT) V23(3):103-107, May 2015. ISSN:2231-2803. www.ijcttjournal.org. Published by Seventh Sense Research Group.

Abstract -
Systems now days are requiring huge database and massive power of computation. This cannot be gained using the available computation technology or computers. Execution time and large data processing are problems which are usually encountered in highly demanded applications such as multimedia processing. Grid computing technology offers a possible solution for computational intensive applications. Canny edge detection algorithm is known as the optimum algorithm for edge detection that performs edge detection in five different and computationally extensive stages, which consume large processing time. In this work, grid computing is used to perform Canny edge detection as an application of grid computing in multimedia processing. Univa grid engine is used the middleware for the proposed grid system. It is demonstrated here that the proposed grid based solution that integrates grid computing technology into Canny edge detection reduces the processing time while preserving the expected performance of Canny edge detection. The time reduction factor is about three times for the adopted grid system and may become better with careful selection of the communication networks technology.

References
[1] R. Al-Khannak and B. Bitzer, “Grid Computing as an Innovative Solution for Power System’s Reliability and Redundancy”, International Conference on Clean Electrical Power , Capri, June 2009.
[2] R. Al-Khannak and B. Bitzer, “Grid Computing for Power and Automation Systems Implementations”, IEEE Universities Power Engineering Conference UPEC’06, Newcastle-upon-Tyne, U.K., Sept. 2006.
[3] R. Al-Khannak and L. Ye, “Integrating Grid Computing Technology for Developing Power Systems Reliability and Efficiency”, 12th WSEAS International Conference on SYSTEMS, Heraklion, Greece, July 2008.
[4] R.Al-Khannak and B. Bitzer, “Load Balancing for Distributed and Integrated Power Systems Using Grid Computing ”, IEEE International Conference on Clean Electrical Power, Capri , May 2007.
[5] M. Baker , R. Buyya and D. Laforenza , “ Grids and Grid Technologies for Wide-Area Distributed Computing”, Grid Computing and Distributed Systems Laboratory, Department of Computer Science and Software Engineering, University of Melbourne, Melbourne, Australia ,2002.
[6] L. Ferreira , V. Berstis , J. Armstrong ,M. Kendzierski , A. Neukoetter , M. Takagi , R. Bing-Wo , A. Amir , R. Murakawa , O. Hernandez , J. Magowan and N. Bieberstein, “Introduction to Grid Computing with Globus ”, IBM Redbooks, 2nd Edition, IBM Corp., International Technical Support Organization, USA , Sept. 2003 .
[7] S. Pardeshi, C. Patil and S. Dhumale, “Grid Computing Architecture and Benefits”, International Journal of Scientific and Research Publications, Volume-3, Issue 8, August 2013.
[8] P. Rani, “Middleware and Toolkits in Grid Computing”, International Journal of Innovative Technology and Exploring Engineering (IJITEE) Volume-2, Issue-4, March 2013.
[9] C.H Lai and F. Magoules, “Fundamentals of Grid Computing Theory, Algorithms and Technologies”, Chapman & Hall/CRC, Taylor and Francis Group LLC, London UK, 2010.
[10] L. Ferreira, F. Lucchese , T. Yasuda , C. Y. Lee , C. Alexandre , E. Minetto and A. Mungioli , “ Grid Computing in Research and Education”, IBM Redbook, 1st Edition , International Technical Support Organization , IBM Corp. , April 2005.
[11] X. He, J. Li, D. Wei, W. Jia, and Q. Wu, “Canny Edge Detection on a Virtual Hexagonal Image Structure”, Pervasive Computing (JCPC), IEEE International Conference, Tamsui, Taipei, Dec. 2009.
[12] G.T. Shrivakshan, “A Comparison of Various Edge Detection Techniques Used in Image Processing”, IJCSI International Journal of Computer Science Issues, Volume-9, Issue-5, Sept. 2012.
[13] C. Gentsos and N. Vassiliadis, “Real-Time Canny Edge Detection Parallel Implementation for FPGAs”, Electronics, Circuits, and Systems (ICECS), IEEE International Conference, Athens, Dec. 2010.
[14] Grid Engine, “Univa Products Grid Engine Software for Workload Scheduling and Management”, Retrieved Oct. 2014. [Online] Available http://www.univa.com/products/grid-engine
[15] Univa Engineering, “Grid Engine Installation Guide”, Grid Engine Documentation, Univa Corporation, Version: 8.2.0, August 2014.
[16] Univa Engineering, “Grid Engine Users’ Guide”, Grid Engine Documentation, Univa Corporation, Version: 1.00, March 2014.
[17] U. Shankar, “Oracle Grid Engine User Guide”, Oracle Company, Release 6.2 Update 7, August 2011.
[18] A. Huamán , B. Gábor , W. Kienzle , E. Christiansen, A. Pavlenko , B. Demiröz, M. Cosenza , V. Glumov , A. Myagkov, E. Feicho and A. Smorkalov, “The OpenCV Tutorials”, Release 2.4.9.0, OpenCV.org, June 2014.
[19] SPRING 4K (ULTRA HD), mp4 video sample, downloaded on March 2014. [Online] Available: http://share2.earthlinktele.com/sharefiles.aspx?file=730831559

Keywords
Grid Computing, Canny Edge Detector, Univa grid engine.