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Stefan cel Mare
University of Suceava
Faculty of Electrical Engineering and
Computer Science
13, Universitatii Street
Suceava - 720229
ROMANIA

Print ISSN: 1582-7445
Online ISSN: 1844-7600
WorldCat: 643243560
doi: 10.4316/AECE


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  4/2011 - 7

 HIGH-IMPACT PAPER 

An Optimal Initial Partitioning of Large Data Model in Utility Management Systems

CAPKO, D. See more information about CAPKO, D. on SCOPUS See more information about CAPKO, D. on IEEExplore See more information about CAPKO, D. on Web of Science, ERDELJAN, A. See more information about  ERDELJAN, A. on SCOPUS See more information about  ERDELJAN, A. on SCOPUS See more information about ERDELJAN, A. on Web of Science, POPOVIC, M. See more information about  POPOVIC, M. on SCOPUS See more information about  POPOVIC, M. on SCOPUS See more information about POPOVIC, M. on Web of Science, SVENDA, G. See more information about SVENDA, G. on SCOPUS See more information about SVENDA, G. on SCOPUS See more information about SVENDA, G. on Web of Science
 
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Download PDF pdficon (608 KB) | Citation | Downloads: 1,484 | Views: 4,813

Author keywords
partitioning algorithms, SCADA systems, power system management, load flow, parallel processing

References keywords
partitioning(10), parallel(8), computing(6), graph(5), systems(4), power(4), multilevel(4), ipdps(4), graphs(4), distributed(4)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2011-11-30
Volume 11, Issue 4, Year 2011, On page(s): 41 - 46
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2011.04007
Web of Science Accession Number: 000297764500007
SCOPUS ID: 84856622601

Abstract
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Modern Utility Management Systems which utilize multiprocessor systems for efficient processing of large data model are considered in this paper. The necessary preconditions for the efficient calculation are optimal load balancing of processors and data model partitioning among processors. The novel multilevel Super-Roots (SR) algorithm was developed to improve existing algorithms (e. i. METIS) for initial partitioning of data model. The proposed algorithms are applied on data model describing large electricity power distribution network. Experiments show that SR algorithm achieves better results than METIS multilevel algorithm in many cases.


References | Cited By  «-- Click to see who has cited this paper

[1] Utility Management Systems (UMS) Data Access Facility DAF, OMG Specification, Version 2.0.1, 2005.

[2] M. Craus, C. Bulancea, "Using Agent Technology Combined with ACO Metaheuristics on Load Balancing Algorithms", Advances in Electrical and Computer Engineering, vol. 4, no. 2, pp. 55-59, 2004.

[3] K. Schloegel, G. Karypis, V. Kumar, "Graph Partitioning for High Performance Scientific Simulations", Technical Report, University of Minesota, 2000.

[4] B. Henderson, T. G. Kolda, "Graph partitioning models for parallel computing", Parallel Computing, vol. 26, no. 12, pp. 1519-1534, 2000.
[CrossRef] [Web of Science Times Cited 234] [SCOPUS Times Cited 318]


[5] M. R. Garey, D. S. Johnson, "Computers and Intractability: A Guide to the Theory of NP-Completeness", W.H.Freeman, San Francisco, 1979.

[6] B. W. Kernighan, S. Lin, "An efficient heuristic procedure for partitioning graphs", The Bell System Technical Journal, vol. 49, no. 2, pp. 291-307, 1970.

[7] C. M. Fiduccia, R. M. Mattheyses, "A linear time heuristic for improving network partitions", In: Proc. 19th IEEE Design Automation Conference, pp. 175-181, 1982.
[CrossRef] [SCOPUS Times Cited 1539]


[8] G. Karypis, V. Kumar, "A fast and high quality multilevel scheme for partitioning irregular graphs", SIAM Journal of Scientific Computing, vol. 20, no. 1, pp. 359-392, 1998.
[CrossRef] [Web of Science Times Cited 3011] [SCOPUS Times Cited 3981]


[9] Henderson, B., Leland, R., "A Multilevel Algorithm for Partitioning Graphs", Proceedings of ACM/IEEE conference on Supercomputing, San Diego, 1995.
[CrossRef] [SCOPUS Times Cited 167]


[10] C. Walshaw, M. Cross, "JOSTLE: Parallel Multilevel Graph-Partitioning Software - An Overview". In F. Magoules, editor, Mesh Partitioning Techniques and Domain Decomposition Techniques, pp. 27-58, Civil-Comp Ltd, 2007.

[11] F. Pellegrini, J. Roman, "SCOTCH: A software package for static mapping by dual recursive bipartitioning of process and architecture graphs", HPCN-Europe, Springer LNCS 1067, pp. 493-498, 1996.
[CrossRef] [SCOPUS Times Cited 277]


[12] H. Meyerhenke, B. Monien, S. Schamberger, "Accelerating shape optimizing load balancing for parallel FEM simulations by algebraic multigrid", In Proc.20th Intl. Parallel and Distributed Processing Symposium (IPDPS'06). IEEE, 2006.
[CrossRef] [SCOPUS Times Cited 27]


[13] Cybenko, G., "Dynamic load balancing for distributed memory multiprocessors", Journal of Parallel and Distributed Computing., vol. 7, no. 2, pp. 279-301, 1989.
[CrossRef] [Web of Science Times Cited 568] [SCOPUS Times Cited 747]


[14] H. Meyerhenke, B Monien, T. Sauerwald, "A new diffusion-based multilevel algorithm for computing graph partitions of very high quality", In: Proceedings of the 22nd International Parallel and Distributed Processing Symposium (IPDPS'08), IEEE Computer Society, pp. 1-13, 2008.
[CrossRef] [SCOPUS Times Cited 35]


[15] IEC 61970 Energy management system application program interface (EMS-API) - Part 301: Common Information Model (CIM) Base, IEC, Edition 2.0, 2007.

[16] D. Capko, A. Erdeljan, M. Popovic, G. Svenda, "An Optimal Relationship-Based Partitioning of Large Datasets", 14th East-European Conference on Advances in Databases and Information Systems, Novi Sad, Serbia, 2010.

[17] C. Godsil, G. Royle, Algebraic Graph Theory, Springer Verlag, 2001.
[CrossRef]


[18] A. Grama, A. Gupta, G. Karypis, V. Kumar, Introduction to Parallel Computing, Second Edition, Addison Wesley, 2003.

[19] R. E. Korf, "A Complete Anytime Algorithm for Number Partitioning", Artificial Intelligence, vol.106, no. 2, pp.181-203, 1998.
[CrossRef] [Web of Science Times Cited 102] [SCOPUS Times Cited 134]


[20] R. E. Korf, "Multi-Way Number Partitioning", International Joint Conference on Artificial Intelligence, Pasadena, California, US, 2009.

[21] M. Popovic, I. Basicevic, V. Vrtunski, "A Task Tree Executor: New Runtime for Parallelized Legacy Software", 16th Annual IEEE International Conference and Workshop on the Engineering of Computer Based Systems, ECBS 2009, San Francisco, USA, 2009.
[CrossRef] [Web of Science Times Cited 3] [SCOPUS Times Cited 13]


[22] D. Shirmohammadi, H. W. Hong, A. Semlyen, G. X. Luo, "A Compensation-Based Power Flow Method For Weakly Meshed Distribution And Transmission Networks", IEEE Transactions on Power Systems, vol. 3, no. 2, pp. 753-762, 1988.
[CrossRef] [Web of Science Times Cited 740] [SCOPUS Times Cited 1001]


[23] B. Allaoua, A. Laoufi, "Optimal Power Flow Solution Using Ant Manners for Electrical Network", Advances in Electrical and Computer Engineering, vol. 9, no. 2, pp. 34-40, 2009.
[CrossRef] [Full Text] [Web of Science Times Cited 25] [SCOPUS Times Cited 35]


[24] G. Grigoras, G. Cartina, E. C. Bobric, "Strategies for Power/Energy Saving in Distribution Networks", Advances in Electrical and Computer Engineering, vol. 9, no.1, pp. 61-64, 2010.
[CrossRef] [Full Text] [Web of Science Times Cited 11] [SCOPUS Times Cited 13]


References Weight

Web of Science® Citations for all references: 4,694 TCR
SCOPUS® Citations for all references: 8,287 TCR

Web of Science® Average Citations per reference: 196 ACR
SCOPUS® Average Citations per reference: 345 ACR

TCR = Total Citations for References / ACR = Average Citations per Reference

We introduced in 2010 - for the first time in scientific publishing, the term "References Weight", as a quantitative indication of the quality ... Read more

Citations for references updated on 2024-07-14 13:39 in 96 seconds.




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