Algorithms with improved delay for enumerating connected induced subgraphs of a large cardinality

Shanshan Wang, Chenglong Xiao, E. Casseau
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Abstract

The problem of enumerating all connected induced subgraphs of a given order $k$ from a given graph arises in many practical applications: bioinformatics, information retrieval, processor design,to name a few. The upper bound on the number of connected induced subgraphs of order $k$ is $n\cdot\frac{(e\Delta)^{k}}{(\Delta-1)k}$, where $\Delta$ is the maximum degree in the input graph $G$ and $n$ is the number of vertices in $G$. In this short communication, we first introduce a new neighborhood operator that is the key to design reverse search algorithms for enumerating all connected induced subgraphs of order $k$. Based on the proposed neighborhood operator, three algorithms with delay of $O(k\cdot min\{(n-k),k\Delta\}\cdot(k\log{\Delta}+\log{n}))$, $O(k\cdot min\{(n-k),k\Delta\}\cdot n)$ and $O(k^2\cdot min\{(n-k),k\Delta\}\cdot min\{k,\Delta\})$ respectively are proposed. The first two algorithms require exponential space to improve upon the current best delay bound $O(k^2\Delta)$\cite{4} for this problem in the case $k>\frac{n\log{\Delta}-\log{n}-\Delta+\sqrt{n\log{n}\log{\Delta}}}{\log{\Delta}}$ and $k>\frac{n^2}{n+\Delta}$ respectively.
具有改进延迟的大基数连通诱导子图枚举算法
从给定图中枚举给定顺序的所有连接的诱导子图$k$的问题出现在许多实际应用中:生物信息学,信息检索,处理器设计,仅举几例。阶为$k$的连通诱导子图个数的上界为$n\cdot\frac{(e\Delta)^{k}}{(\Delta-1)k}$,其中$\Delta$为输入图$G$中的最大度,$n$为$G$中的顶点数。在这篇简短的通信中,我们首先引入了一个新的邻域算子,它是设计反向搜索算法的关键,用于枚举顺序为$k$的所有连接的诱导子图。基于所提出的邻域算子,提出了延迟分别为$O(k\cdot min\{(n-k),k\Delta\}\cdot(k\log{\Delta}+\log{n}))$、$O(k\cdot min\{(n-k),k\Delta\}\cdot n)$和$O(k^2\cdot min\{(n-k),k\Delta\}\cdot min\{k,\Delta\})$的三种算法。在$k>\frac{n\log{\Delta}-\log{n}-\Delta+\sqrt{n\log{n}\log{\Delta}}}{\log{\Delta}}$和$k>\frac{n^2}{n+\Delta}$的情况下,前两种算法需要指数空间来改进当前最佳延迟界$O(k^2\Delta)$\cite{4}。
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