WRS (Waiting Room Sampling) is a single-pass streaming algorithm for global and local triangle counting in (fully dynamic) real graph streams. WRS exploits a temporal dependency pattern in real dynamic graph streams. WRS has the following properties:

• fast and any time: WRS scales linearly with the number of edges in the input graph stream, and gives estimates at any time while the input graph grows
• effective: estimation error in WRS is up to 47% smaller than those in state-of-the-art methods
• theoretically sound: WRS gives unbiased estimates with small variance under the temporal locality.

The download links for the datasets used in the paper are here

Please see User Guide

For demo, please type 'make'

If you use this code as part of any published research, please acknowledge the following paper.

@inproceedings{shin2017wrs,
  author       = {Kijung Shin},
  title        = {WRS: Waiting Room Sampling for Accurate Triangle Counting in Real Graph Streams},
  booktitle    = {ICDM},
  pages        = {1087--1092},
  year         = {2017},
  organization = {IEEE}
}

@article{lee2020temporal,
  title     = {Temporal locality-aware sampling for accurate triangle counting in real graph streams},
  author    = {Lee, Dongjin and Shin, Kijung and Faloutsos, Christos},
  journal   = {The VLDB Journal},
  volume    = {29},
  number    = {6},
  pages     = {1501--1525},
  year      = {2020},
  publisher = {Springer}
}