Efficient Solutions For Finding Vitality With Respect To Shortest Paths

被引:0
|
作者
Kare, Anjeneya Swami [1 ]
Saxena, Sanjeev [2 ]
机构
[1] Univ Hyderabad, Sch Comp & Informat Sci, Hyderabad 500046, Andhra Pradesh, India
[2] Indian Inst Technol, Dept Comp Sci & Engn, Kanpur 208016, Uttar Pradesh, India
来源
2013 SIXTH INTERNATIONAL CONFERENCE ON CONTEMPORARY COMPUTING (IC3) | 2013年
关键词
Most Vital Edge; Most Vital Node; Replacement Shortest Path; Vickrey Pricing; REPLACEMENT PATHS; EDGE; ALGORITHMS; SINGLE;
D O I
暂无
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Let G = (V; E) be a connected, weighted, undirected graph such that vertical bar V vertical bar = n and vertical bar E vertical bar = m. Given a shortest path P-G (s; t) between a source node s and a sink node t in the graph G, computing the shortest path between source and sink without using a particular edge (or a particular node) in P-G (s; t) is called Replacement Shortest Path for that edge (or node). The Most Vital Edge (MVE) problem is to find an edge in P-G (s; t) whose removal results in the longest replacement shortest path. And the Most Vital Node (MVN) problem is to find a node in P G (s; t) whose removal results in the longest replacement shortest path. In this paper for the MVE problem we describe an O (m + m' alpha (m'; n')) time algorithm (alpha represents Inverse Ackermann function) by constructing a smaller graph L G from G which we call Linear Graph, where n' and m' are the number of nodes and edges in L-G respectively. Our algorithm will also suggest a replacement shortest path for every edge in P-G (s; t) without any additional time. For the MVN problem, with integer weights, we describe an O (m alpha(m; n)) time algorithm. Our algorithm will also suggest a replacement shortest path for every node in P-G (s; t) without any additional time.
引用
收藏
页码:70 / 75
页数:6
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