自己修復デモの操作手順(Procedure of the self-healing demonstration)
Step1
- 左上のメニューから、.net形式の入力ファイルを選ぶ。
- 注：別の入力で試すには、"Refresh Graph"ボタンを押してからして下さい。
- (Chose an input file.net as a network-data from the top menue at left-side.)
- (Cuation: It is necessary to push "Refresh Graph" before trying another input file.)
Step2
- 同様に左の2番目と3番目のメニューから、攻撃法と描画法を選ぶ。
- (Similarly, chose an attack method and a graph layout from the 2nd and 3rd menues at left-side, respectively.)
Step3
- 左中央付近のスライドバーで、攻撃率と修復率をそれぞれ設定する。
- (Set parameter values of attack and heal rates by moving slide vars around the middle at left-side, respectively.)
Step4
- 上記の準備の後、"Draw Graph"ボタンを押す。
- (Push ”Draw Graph" button after the above preparing.)
Step5
- 上すると、その結果が右に可視化される。赤線が修復リンク、黒線が元のリンクを表す。 また、ノード数とリンク数の差を左下に、次数分布の差を右下にヒストグラムで示す。
- (Then, the result with red healing and black original links are drawn at right-side. Moreover, the histograms show the differences of numbers of nodes or links at left-side bottom, and of degree distributions at right-side bottom.)
さぁ、DASHボタンを押して自己修復のデモを試してみましょう !もしグルグル表示が続くなら、Refresh後に再試行して下さい。
- (Let's try it by clicking the link below ! If you eoncounter spinning wheel, please retry after Refresh.)
- DASH
Input Files:
N denotes the size (# of total nodes), Norm means the area normalization.Synthetic Networks:
SF_BA_N200_m4.net Generaled by BA model for m=4 links per time-step.IPA_-10_N200_m4.net Generaled by IPA model for \beta=-10 and m=4 links per time-step.
IPA_-100_N200_m4.net Generaled by IPA model for \beta=-100 and m=4 links per time-step.
Real Communication Networks:
ATT_US_Norm.net Communication network constructed by AT&T Co.Ltd in USACost266_Norm.net Communication network in EU
Janos-us-ca_Norm.net a part of communication network between USA and Canada
Germany50.net Communication network around Germany
Coronet.net Communication network in USA
References for BA and IPA models
・A.-L.Barabási, R.Albert, and H.Jeong, "Mean-field theory for scale-free random networks" Physica A 272, pp.173-187 (1999).・L.Fuxuan, and Y.Hayashi, "Emergence of Robust and Efficient Networks in a Family of Attachment Models" Physica A 599, 127427, (2022).
Implemented by S.K.
