Earticle

초록

영어

Spectral density approach for distinguishing graphs was studied in this paper. Firstly, Spectral density approach was testified for being effective in distinguishing different graphs by making comparisons among the spectrums of three different kind of graphs, the ER random graph, BA scale-free graph and the Internet topology graph. Secondly, we focused our studies on the properties of Internet graph that its spectrum could represent, and found that in standard spectral density analysis part, we found that the spectral density plot of Internet graph has a feature of having a maximum when λ=0 and the second maximum whenλ=0.5 around. In SLS analysis part, we found the SLS spectrum had a set of highest tuples when SLS=1 and second highest tuples when SLS=2. Besides, a relationship of the power law distribution was observed when SLS>2, but there is no power-law relationship found when SLS<1. What was found here could be used to identify an Internet topology graph properties.

목차

Abstract
 1. Introduction
  1.1 Spectral density introduction
  1.2 Experiment samples
  1.3 Internet topology graph re-sampling tool
 2. Experiments of spectrum in distinguishing topology graphs
 3. Spectral density approach in Internet topology research
  3.1. Normal spectral density analysis
  3.2. SLS
 4. Conclusions
 References

저자

• XU Ye [ College of Information Science and Engineering, Shenyang Ligong University, Shenyang, China ]
• WANG Zhuo [ College of Information Science and Engineering, Shenyang Ligong University, Shenyang, China ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Hybrid Information Technology

• 간기

  격월간

• pISSN

  1738-9968

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605