E cient Algorithm for Computing All Low s-t Edge Connectivities in Directed Graphs

نویسندگان

  • Xiaowei Wu
  • Chenzi Zhang
چکیده

Given a directed graph with n nodes andm edges, the (strong) edge connectivity λ(u, v) between two nodes u and v is the minimum number of edges whose deletion makes u and v not strongly connected. The problem of computing the edge connectivities between all pairs of nodes of a directed graph can be done in O(m) time by Cheung, Lau and Leung (FOCS 2011), where ω is the matrix multiplication factor (≈ 2.373), or in Õ(mn) time using O(n) computations of maxows by Cheng and Hu (IPCO 1990). We consider in this paper the low edge connectivity problem, which aims at computing the edge connectivities for the pairs of nodes (u, v) such that λ(u, v) ≤ k. While the undirected version of this problem was considered by Hariharan, Kavitha and Panigrahi (SODA 2007), who presented an algorithm with expected running time Õ(m+nk), no algorithm better than computing all-pairs edge connectivities was proposed for directed graphs. We provide an algorithm that computes all low edge connectivities in O(kmn) time, improving the previous best result of O(min(m,mn)) when k ≤ √ n. Our algorithm also computes a minimum u-v cut for each pair of nodes (u, v) with λ(u, v) ≤ k.

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Efficient Algorithm for Computing All Low s-t Edge Connectivities in Directed Graphs

Given a directed graph with n nodes andm edges, the (strong) edge connectivity λ(u, v) between two nodes u and v is the minimum number of edges whose deletion makes u and v not strongly connected. The problem of computing the edge connectivities between all pairs of nodes of a directed graph can be done in O(m) time by Cheung, Lau and Leung (FOCS 2011), where ω is the matrix multiplication fact...

متن کامل

Efficient algorithms for computing all low s-t edge connectivities and related problems

Given an undirected unweighted graph G = (V, E) and an integer k ≥ 1, we consider the problem of computing the edge connectivities of all those (s, t) vertex pairs, whose edge connectivity is at most k. We present an algorithm with expected running time Õ(m + nk) for this problem, where |V | = n and |E| = m. Our output is a weighted tree T whose nodes are the sets V1, V2, . . . , V` of a partit...

متن کامل

Computing Szeged index of graphs on ‎triples

ABSTRACT Let ‎G=(V,E) ‎be a‎ ‎simple ‎connected ‎graph ‎with ‎vertex ‎set ‎V‎‎‎ ‎and ‎edge ‎set ‎‎‎E. ‎The Szeged index ‎of ‎‎G is defined by ‎ where ‎ respectively ‎ ‎ is the number of vertices of ‎G ‎closer to ‎u‎ (‎‎respectively v)‎ ‎‎than ‎‎‎v (‎‎respectively u‎).‎ ‎‎If ‎‎‎‎S ‎is a‎ ‎set ‎of ‎size‎ ‎ ‎ ‎let ‎‎V ‎be ‎the ‎set ‎of ‎all ‎subsets ‎of ‎‎S ‎of ‎size ‎3. ‎Then ‎we ‎define ‎t...

متن کامل

On the revised edge-Szeged index of graphs

The revised edge-Szeged index of a connected graph $G$ is defined as Sze*(G)=∑e=uv∊E(G)( (mu(e|G)+(m0(e|G)/2)(mv(e|G)+(m0(e|G)/2) ), where mu(e|G), mv(e|G) and m0(e|G) are, respectively, the number of edges of G lying closer to vertex u than to vertex v, the number of ed...

متن کامل

A note on vertex-edge Wiener indices of graphs

The vertex-edge Wiener index of a simple connected graph G is defined as the sum of distances between vertices and edges of G. Two possible distances D_1(u,e|G) and D_2(u,e|G) between a vertex u and an edge e of G were considered in the literature and according to them, the corresponding vertex-edge Wiener indices W_{ve_1}(G) and W_{ve_2}(G) were introduced. In this paper, we present exact form...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2015