원문정보
보안공학연구지원센터(IJFGCN)
International Journal of Future Generation Communication and Networking
Vol.7 No.4
2014.08
pp.119-126
피인용수 : 0건 (자료제공 : 네이버학술정보)
초록
영어
A complex network is a interaction network of entities where global behavior is not deductible from the individual behaviors of each entities, leading to new properties emergence. Our problem is the network analysis ad modeling. Network analysis needs a formalism to assemble together the structure (static approach) and the function (dynamic approach), and to have a better understanding of the networks characteristics. In this paper, we introduce common used network modeling based on graph theory, having the role to simulate complex networks.
목차
Abstract
1. Introduction
1.1. Definition
1.2. Complex Networks Behavior
2. Complex Networks Classification
2.1. Social Networks
2.2. Information Networks
2.3. Technological Network
2.4. Biological Network
3. Modeling of Complex Networks
3.1. Graph Theory
4. News Characteristics
4.1. Clustering Coefficient
4.2. Degree of Correlation
4.3. Assortativity
4.4. Small Diameter
5. Existing Models
5.1. Erdös & Rémi
5.2. Albert & Burabassi
5.3. Watts & Strogatz
5.4. Kleinberg
6. Axes Research in Complex Networks
7. Conclusion
References
1. Introduction
1.1. Definition
1.2. Complex Networks Behavior
2. Complex Networks Classification
2.1. Social Networks
2.2. Information Networks
2.3. Technological Network
2.4. Biological Network
3. Modeling of Complex Networks
3.1. Graph Theory
4. News Characteristics
4.1. Clustering Coefficient
4.2. Degree of Correlation
4.3. Assortativity
4.4. Small Diameter
5. Existing Models
5.1. Erdös & Rémi
5.2. Albert & Burabassi
5.3. Watts & Strogatz
5.4. Kleinberg
6. Axes Research in Complex Networks
7. Conclusion
References
저자정보
참고문헌
자료제공 : 네이버학술정보