Compression of Dynamic Graphs Generated by a Duplication Model

Author:

Turowski Krzysztof,Magner Abram,Szpankowski Wojciech

Abstract

AbstractWe continue building up the information theory of non-sequential data structures such as trees, sets, and graphs. In this paper, we consider dynamic graphs generated by a full duplication model in which a new vertex selects an existing vertex and copies all of its neighbors. We ask how many bits are needed to describe the labeled and unlabeled versions of such graphs. We first estimate entropies of both versions and then present asymptotically optimal compression algorithms up to two bits. Interestingly, for the full duplication model the labeled version needs $$\Theta (n)$$ Θ ( n ) bits while its unlabeled version (structure) can be described by $$\Theta (\log n)$$ Θ ( log n ) bits due to significant amount of symmetry (i.e. large average size of the automorphism group of sample graphs).

Funder

National Science Foundation

Publisher

Springer Science and Business Media LLC

Subject

Applied Mathematics,Computer Science Applications,General Computer Science

Cited by 3 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. A Universal Low Complexity Compression Algorithm for Sparse Marked Graphs;IEEE Journal on Selected Areas in Information Theory;2022-12

2. Temporal Ordered Clustering in Dynamic Networks: Unsupervised and Semi-Supervised Learning Algorithms;IEEE Transactions on Network Science and Engineering;2021-04-01

3. Towards Degree Distribution of a Duplication-Divergence Graph Model;The Electronic Journal of Combinatorics;2021-01-29

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