Fast and Accurate Graph Stream Summarization

TL;DR

This paper introduces Graph Stream Sketch (GSS), a novel method for summarizing dynamic graph streams efficiently, supporting all query types with high accuracy, low space, and constant update time.

Contribution

The paper presents GSS, a new graph stream summarization technique that improves accuracy and efficiency over existing methods, supporting all query types with linear space and constant update time.

Findings

GSS achieves higher query accuracy than prior methods.

GSS operates with linear space complexity and O(1) update time.

Experimental results confirm GSS's superiority in speed and precision.

Abstract

A graph stream is a continuous sequence of data items, in which each item indicates an edge, including its two endpoints and edge weight. It forms a dynamic graph that changes with every item in the stream. Graph streams play important roles in cyber security, social networks, cloud troubleshooting systems and other fields. Due to the vast volume and high update speed of graph streams, traditional data structures for graph storage such as the adjacency matrix and the adjacency list are no longer sufficient. However, prior art of graph stream summarization, like CM sketches, gSketches, TCM and gMatrix, either supports limited kinds of queries or suffers from poor accuracy of query results. In this paper, we propose a novel Graph Stream Sketch (GSS for short) to summarize the graph streams, which has the linear space cost (O(|E|), E is the edge set of the graph) and the constant update time complexity (O(1)) and supports all kinds of queries over graph streams with the controllable errors. Both theoretical analysis and experiment results confirm the superiority of our solution with regard to the time/space complexity and query results' precision compared with the state-of-the-art.