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Evaluating space-efficient algorithms for detecting large neighbourhoods in graph streams

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Detecting-Large-Neighbourhoods-in-Graph-Streams

Streaming Frequent Items with Timestamps and Detecting Large Neighbourhoods in Graph Streams

Compiling

g++ insertionStreams.cpp -o is g++ insertionDeletionStreams.cpp -o ids

Execution

is
ids

Data

Graphs are stored as a stream of edges, in no particular order.
Each line represents an edge with a space separating each node id.

Natural (Found on snap.stanford.edu/data)

Graph Name Type # Edges # Vertices Max Degree File Size
facebook_small Insertion-Only 292 52 36 3 KB
facebook_small_deletion Insertion-Deletion 326 52 33 5 KB
facebook Insertion-Only 60,050 747 586 587 KB
facebook_deletion Insertion-Deletion 66,643 747 522 846 KB
gplus Insertion-Only 1,179,613 12,417 5,948 52,839 KB
gplus_deletion Insertion-Deletion 1,309,917 12,417 4,998 60,124 KB
gplus_large Insertion-Only 30,238,035 102,100 104,947 1,328,820 KB

Artificial (Generated by my programs).

Graph Name Type # Edges # Vertices Max Degree File Size
1000vertices Insertion-Only 246,676 1,000 984 2,119 KB
test_deletion Insertion-Deletion 216,319 1,000 484 5,256 KB
test_deletion_double Insertion-Deletion 125,026 1,000 515 4,404 KB

NOTE - For Insertion-Deletion Graphs: '# Edges' refers to the final number of edges in the graph after a full stream; '# Vertices' refers to the number of different vertices encountered during the whole stream so some vertices may have 0-degree after the stream has finished.

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Evaluating space-efficient algorithms for detecting large neighbourhoods in graph streams

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