Paper Titles

Sparse Representation De-Noising Based on Morlet Wavelet Basis and its Application for Transient Feature Extraction
p.200

Structure Design and Analysis of Moving Character for Detect Robot for Underground Coal Mine
p.205

Design of a Magnetic Wall-Climbing Car
p.211

Finite Element Analysis of the Overturning Process of Ring-Stiffened Titanium Shperical-Cylindrica Diaphragm for Positive Expulsion Tanks
p.217

Study on Community Structures in Manufacturing Grid and the Algorithm for Community Partition of its Resource Nodes
p.222

The Gears System Reliability Analysis with Correlation among the Components of Gear Box in Self-Propelled Gun
p.230

Study on the Multi-Tooth Meshing Bending Strength for Involute Gear Drive with Small Tooth Number Difference
p.236

Fabrication and Experimental Investigation of a Novel 3D Hydrodynamic Focusing Micro Cytometric Device
p.242

Analysis on Shaft Failure of the Twin Screw Pump
p.253

HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vol. 526Study on Community Structures in Manufacturing...

Study on Community Structures in Manufacturing Grid and the Algorithm for Community Partition of its Resource Nodes

Article Preview

Abstract:

The Manufacturing Grid supplies a public platform for global resource sharing, collaborative design and manufacturing; its resource nodes constitute a complex network. Community partition of the complex network composed of the manufacturing resource nodes may be of some benefit for the sharing of manufacturing resources efficiently. In this paper, the resource nodes in the Manufacturing Grid are treated as the nodes of the complex network and the node-to-node link as its edges or arcs. The features of the resource nodes are analyzed based on which a model of the complex network composed of resource nodes in the Manufacturing Grid is set up. The nature phenomenon of the community structure in the complex network of manufacturing resource nodes is described according to the division of the manufacturing task into subtasks. Referring to Newmans idea, a criterion to evaluate the partition of community structure is discussed. Then, an improved algorithm based on Newman's Fast Algorithm is put forward to partition the community. The algorithm fully considers the characteristics of the direction and weight in the complex network for manufacturing resource nodes. Examples show that the algorithm presented in the paper can partition the community with favorable results.

You might also be interested in these eBooks

Mechanical Engineering and Instrumentation

Info:

Periodical:

Applied Mechanics and Materials (Volume 526)

Pages:

222-229

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.526.222

Citation:

Cite this paper

Online since:

February 2014

Authors:

Yong Yin*, Yu Li, Chao Yong Zhang

Keywords:

Community Partition, Complex Network, Manufacturing Grid, Resource Nodes

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

© 2014 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

* - Corresponding Author

[1] Foster I, Kesselman C, Tuecke S (2001). The anatomy of the grid [J]. Int J Supercomput Appl 15(3): 1-21.

[2] F. Tao, Y. Hu and Z. D. Zhou. An approach to manufacturing grid resource service scheduling based on trust-QoS. International Journal of Computer Integrated Manufacturing, 2009. 22(2): 100-111.

DOI: 10.1080/09511920802139875

[3] Yong Yin, Zude Zhou, Youping Chen, Yihong Long. Information service of the resource node in a manufacturing grid environment [J]. Int J Adv Manuf Technol, (2008)39: 409-413.

DOI: 10.1007/s00170-007-1209-3

[4] S. H. Strogatz, D. J. Watts. Collective dynamics of small-world, networks. Nature, 1998(393): 440-442.

DOI: 10.1038/30918

[5] R. Albert and A. L. Barabasi, Statistical mechanics of complex networks. Reviews of Modern Physics, 2002(74): 47-97.

[6] L.D. A. F. Costa, F. A. Rodrigues, G. Travieso and P. R. V. Boas, Characterization of complex networks: A survey of measurements. Advances in Physics, 200756(1): 167-242.

DOI: 10.1080/00018730601170527

[7] LUQ. G, LIU D. H, WEI G. Q and LIL. F. Research on Regional Manufacturing Industry Alliance Based on Complex Network. Journal of Nanchang Institute of Technology, 2006. 125(1): 10-13.

[8] WANG J. F, WANG G, WEN X. X. Statistics of collaborative manufacturing resource based on complex networks. Machinery Design＆Manufacture 2009(1): 185-186.

[9] ZHONG G. J, SUI R. B. Research on networks of parts relation for product family based on complex networks. Journal of Harbin University of Commerce (Natural Science Edition), 2009. 25(2): 253-256.

[10] Newman M E J, Girvan M. Finding and evaluating community structure in networks [J]. Phys Rev E, 2004, 69(2): 026113.

[11] Newman M E J. Detecting community structure in networks [J]. EurPhys J B, 2004, 38: 321-330.

[12] Reichardt J, Bomholdt S. Statistical mechanics of community detection [J]. Phys Rev E, 2006, 74(1): 016110.

[13] Zhou T, Zhao M, Chen G R. Phase synchronization on scale-free networks with community structure [J]. Phys LettA, 2007, 368: 431-434.

[14] Shihua Z, Rui-Sheng W, Xiang-Sun Z. Identification of overlapping community structure in complex networks using fuzzy c-means clustering [J]. Physica A, 2007. 374: 483-490.

DOI: 10.1016/j.physa.2006.07.023

[15] Junhua Z, Shihua Z, Xiang-Sun Z. Detecting community structure in complex networks based on a measure of information discrepancy [J]. Physica A, 2008. 387: 1675-1682.

DOI: 10.1016/j.physa.2007.10.061

[16] Newman M E J. Analysis of weighted networks [J]. Phys. Rev. E, 2004, 70(5): 056131-056139.

[17] OU You-yuan, ZHANG Hal. su, MENG Hui, LI De-yi. Web services clustering based on detecting community structure in complex network [J]. Application Research of Computers Vol. 26 No. 6 Jun. 2009: 2299-2302.

[18] Rodrigues F A, Travieso G, Costa L F. Fast community identification by hierarchical growth. Arxiv: cond-mat/0602144, 2006. http: /en. scientificcommons. org/21950718.