https://github.com/nemeslaszlo/graphs-system

This repository contains a our work about the "Real-time Constrained Cycle Detection in Large Dynamic Graphs" paper, which present a GraphS system to efficiently detect constrained cycles in a dynamic graph, which is changing constantly, and return the satisfying cycles in real-time.
https://github.com/nemeslaszlo/graphs-system

dynamic-graph-algorithm dynamic-graphs graph java jgrapht

Last synced: about 1 year ago
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This repository contains a our work about the "Real-time Constrained Cycle Detection in Large Dynamic Graphs" paper, which present a GraphS system to efficiently detect constrained cycles in a dynamic graph, which is changing constantly, and return the satisfying cycles in real-time.

• Host: GitHub
• URL: https://github.com/nemeslaszlo/graphs-system
• Owner: NemesLaszlo
• Created: 2020-10-20T08:59:02.000Z (over 5 years ago)
• Default Branch: main
• Last Pushed: 2020-11-20T15:15:27.000Z (over 5 years ago)
• Last Synced: 2025-01-29T08:44:17.839Z (over 1 year ago)
• Topics: dynamic-graph-algorithm, dynamic-graphs, graph, java, jgrapht
• Language: Java
• Homepage: http://www.vldb.org/pvldb/vol11/p1876-qiu.pdf
• Size: 18.6 KB
• Stars: 1
• Watchers: 4
• Forks: 1
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

          
# GraphS-system

This repository contains a our work about the "Real-time Constrained Cycle Detection in Large Dynamic Graphs" paper, which present a GraphS system to efficiently detect constrained cycles in a dynamic graph, which is changing constantly, and return the satisfying cycles in real-time.

From the paper:

### Abstract.

As graph data is prevalent for an increasing number of Internet applications, continuously monitoring structural patterns in dynamic graphs in order to generate real-time alerts

and trigger prompt actions becomes critical for many applications. In this paper, we present a new system GraphS

to efficiently detect constrained cycles in a dynamic graph,

which is changing constantly, and return the satisfying cycles

in real-time. A hot point based index is built and efficiently

maintained for each query so as to greatly speed-up query

time and achieve high system throughput. The GraphS system is developed at Alibaba to actively monitor various online fraudulent activities based on cycle detection. For a

dynamic graph with hundreds of millions of edges and vertices, the system is capable to cope with a peak rate of tens

of thousands of edge updates per second and find all the

cycles with predefined constraints with a 99.9% latency of

20 milliseconds.