(9 graphs) AS peering info inferred from Oregon route-views, 3/31-5/26/01
Name Oregon-2
Group SNAP
Matrix ID 2324
Num Rows 11,806
Num Cols 11,806
Nonzeros 65,460
Pattern Entries 65,460
Kind Undirected Graph Sequence
Symmetric Yes
Date 2001
Author J. Leskovec, J. Kleinberg and C. Faloutsos
Editor J. Leskovec
Structural Rank
Structural Rank Full
Num Dmperm Blocks
Strongly Connect Components 346
Num Explicit Zeros 0
Pattern Symmetry 100%
Numeric Symmetry 100%
Cholesky Candidate no
Positive Definite no
Type binary
SVD Statistics
Matrix Norm 7.524069e+01
Minimum Singular Value 0
Condition Number Inf
Rank 3,825
Null Space Dimension 7,981
Full Numerical Rank? no
Download Singular Values MATLAB
Download MATLAB Rutherford Boeing Matrix Market
Networks from SNAP (Stanford Network Analysis Platform) Network Data Sets,     
Jure Leskovec                         
email jure at                                                  
Autonomous systems - Oregon-2                                                  
Dataset information                                                            
9 Autonomous systems graphs, 1 per week between March 31 2001 and May 26 2001. 
Graphs represent AS peering information inferred from Oregon route-views,      
Looking glass data, and Routing registry, all combined.                        
Dataset statistics are calculated for the graph with the lowest (March 31 2001)
and highest (from May 26 2001) number of nodes:                                
Dataset statistics for graph with lowest number of nodes - 3 31 2001           
Nodes   10900                                                                  
Edges   31180                                                                  
Nodes in largest WCC    10900 (1.000)                                          
Edges in largest WCC    31180 (1.000)                                          
Nodes in largest SCC    10900 (1.000)                                          
Edges in largest SCC    31180 (1.000)                                          
Average clustering coefficient  0.5009                                         
Number of triangles     82856                                                  
Fraction of closed triangles    0.03855                                        
Diameter (longest shortest path)    9                                          
90-percentile effective diameter    4.3                                        
Dataset statistics for graph with highest number of nodes - 5 26 2001          
Nodes   11461                                                                  
Edges   32730                                                                  
Nodes in largest WCC    11461 (1.000)                                          
Edges in largest WCC    32730 (1.000)                                          
Nodes in largest SCC    11461 (1.000)                                          
Edges in largest SCC    32730 (1.000)                                          
Average clustering coefficient  0.4943                                         
Number of triangles     89541                                                  
Fraction of closed triangles    0.03701                                        
Diameter (longest shortest path)    9                                          
90-percentile effective diameter    4.3                                        
Source (citation)                                                              
J. Leskovec, J. Kleinberg and C. Faloutsos. Graphs over Time: Densification    
Laws, Shrinking Diameters and Possible Explanations. ACM SIGKDD International  
Conference on Knowledge Discovery and Data Mining (KDD), 2005.                 
File    Description                                                            
        AS peering information inferred from Oregon route-views, Looking glass 
        data, and Routing registry,  ...                                       
oregon2_010331.txt.gz from March 31 2001                                       
oregon2_010407.txt.gz from April 7 2001                                        
oregon2_010414.txt.gz from April 14 2001                                       
oregon2_010421.txt.gz from April 21 2001                                       
oregon2_010428.txt.gz from April 28 2001                                       
oregon2_010505.txt.gz from May 05 2001                                         
oregon2_010512.txt.gz from May 12 2001                                         
oregon2_010519.txt.gz from May 19 2001                                         
oregon2_010526.txt.gz from May 26 2001                                         
NOTE: for the UF Sparse Matrix Collection, the primary matrix in this problem  
set (Problem.A) is the last matrix in the sequence, oregon2_010526, from May 26
The nodes are uniform across all graphs in the sequence in the UF collection.  
That is, nodes do not come and go.  A node that is "gone" simply has no edges. 
This is to allow comparisons across each node in the graphs.                   
Problem.aux.nodenames gives the node numbers of the original problem.  So      
row/column i in the matrix is always node number Problem.aux.nodenames(i) in   
all the graphs.                                                                
Problem.aux.G{k} is the kth graph in the sequence.                             
Problem.aux.Gname(k,:) is the name of the kth graph.