The 1-Fixed-Endpoint Path Cover Problem is Polynomial on Interval Graphs

We consider a variant of the path cover problem, namely, the k-fixed-endpoint path cover problem, or kPC for short, on interval graphs. Given a graph G and a subset T\mathcal{T} of k vertices of V(G), a k-fixed-endpoint path cover of G with respect to T\mathcal{T} is a set of vertex-disjoint paths ℘ that covers the vertices of G such that the k vertices of T\mathcal{T} are all endpoints of the paths in ℘. The kPC problem is to find a k-fixed-endpoint path cover of G of minimum cardinality; note that, if T\mathcal{T} is empty the stated problem coincides with the classical path cover problem. In this paper, we study the 1-fixed-endpoint path cover problem on interval graphs, or 1PC for short, generalizing the 1HP problem which has been proved to be NP-complete even for small classes of graphs. Motivated by a work of Damaschke (Discrete Math. 112:49–64, 1993), where he left both 1HP and 2HP problems open for the class of interval graphs, we show that the 1PC problem can be solved in polynomial time on the class of interval graphs. We propose a polynomial-time algorithm for the problem, which also enables us to solve the 1HP problem on interval graphs within the same time and space complexity.     

One-to-one disjoint path covers on multi-dimensional tori

The multi-dimensional torus is one of the most popular underlying topologies for massively parallel systems. In this study, we consider a non-bipartite n-dimensional torus where n≥2 and prove that for 1≤m≤2n, m vertex disjoint paths exist that cover all vertices between any two distinct vertices. In other words, we construct the one-to-one m-disjoint path cover of a non-bipartite torus for any m where 1≤m≤2n.     

Applying Modular Decomposition to Parameterized Cluster Editing Problems

A graph G is said to be a bicluster graph if G is a disjoint union of bicliques (complete bipartite subgraphs), and a cluster graph if G is a disjoint union of cliques (complete subgraphs). In this work, we study the parameterized versions of the NP-hard Bicluster Graph Editing and Cluster Graph Editing problems. The former consists of obtaining a bicluster graph by making the minimum number of modifications in the edge set of an input bipartite graph. When at most k modifications are allowed (Bicluster(k) Graph Editing problem), this problem is FPT, and can be solved in O(4 ^k nm) time by a standard search tree algorithm. We develop an algorithm of time complexity O(4 ^k +n+m), which uses a strategy based on modular decomposition techniques; we slightly generalize the original problem as the input graph is not necessarily bipartite. The algorithm first builds a problem kernel with O(k ²) vertices in O(n+m) time, and then applies a bounded search tree. We also show how this strategy based on modular decomposition leads to a new way of obtaining a problem kernel with O(k ²) vertices for the Cluster(k) Graph Editing problem, in O(n+m) time. This problem consists of obtaining a cluster graph by modifying at most k edges in an input graph. A previous FPT algorithm of time O(1.92 ^k +n ³) for this problem was presented by Gramm et al. (Theory Comput. Syst. 38(4), 373–392, 2005, Algorithmica 39(4), 321–347, 2004). In their solution, a problem kernel with O(k ²) vertices is built in O(n ³) time.     

On the locatic number of graphs

A vertex v of a connected graph G distinguishes a pair u, w of vertices of G if d(v, u)≠d(v, w), where d(·,·) denotes the length of a shortest path between two vertices in G. A k-partition Π={S ₁, S ₂, …, S _k } of the vertex set of G is said to be a locatic partition if for every pair of distinct vertices v and w of G, there exists a vertex s∈S _i for all 1≤i≤k that distinguishes v and w. The cardinality of a largest locatic partition is called the locatic number of G. In this paper, we study the locatic number of paths, cycles and characterize all the connected graphs of order n having locatic number n, n?1 and n?2. Some realizable results are also given in this paper.     

Improved algorithms for the k simple shortest paths and the replacement paths problems

Given a directed, non-negatively weighted graph G=(V,E) and s,t∈V, we consider two problems. In the k simple shortest paths problem, we want to find the k simple paths from s to t with the k smallest weights. In the replacement paths problem, we want the shortest path from s to t that avoids e, for every edge e in the original shortest path from s to t. The best known algorithm for the k simple shortest paths problem has a running of O(k(mn+n²logn)). For the replacement paths problem the best known result is the trivial one running in time O(mn+n²logn).In this paper we present two simple algorithms for the replacement paths problem and the k simple shortest paths problem in weighted directed graphs (using a solution of the All Pairs Shortest Paths problem). The running time of our algorithm for the replacement paths problem is O(mn+n²loglogn). For the k simple shortest paths we will perform O(k) iterations of the second simple shortest path (each in O(mn+n²loglogn) running time) using a useful property of Roditty and Zwick [L. Roditty, U. Zwick, Replacement paths and k simple shortest paths in unweighted directed graphs, in: Proc. of International Conference on Automata, Languages and Programming (ICALP), 2005, pp. 249-260]. These running times immediately improve the best known results for both problems over sparse graphs.Moreover, we prove that both the replacement paths and the k simple shortest paths (for constant k) problems are not harder than APSP (All Pairs Shortest Paths) in weighted directed graphs.     

The k-neighbourhood-covering problem on interval graphs

Let G=(V, E) be a simple connected graph and k be a fixed positive integer. A vertex w is said to be a k-neighbourhood-cover (kNC) of an edge (u, v) if d(u, w)≤k and d(v, w)≤k. A set C ? V is called a kNC set if every edge in E is kNC by some vertices of C. The decision problem associated with this problem is NP-complete for general graphs and it remains NP-complete for chordal graphs. In this article, we design an O(n) time algorithm to solve minimum kNC problem on interval graphs by using a data structure called interval tree.     

Design of 4-disjoint gamma interconnection network layouts and reliability analysis of gamma interconnection Networks

Multistage interconnection networks (MINs) are widely used for reliable data communication in a tightly coupled large-scale multiprocessor system. High reliability of MINs can be achieved using fault tolerance techniques. The fault tolerance is generally achieved by disjoint paths available through multiple connectivity options. The gamma interconnection network (GIN) is a class of fault tolerant MINs providing alternate paths for source–destination node pairs. Various 2-disjoint and 3-disjoint GIN architectures have been presented in the literature. In this paper, two new designs of 4-disjoint paths multistage interconnection networks, called 4-disjoint gamma interconnection networks (4DGIN-1 and 4DGIN-2) are proposed. The proposed 4DGINs provide four disjoint paths for each source–destination pair and can tolerate three switches/link failures in intermediate interconnection layers. Proposed designs are highly reliable GIN with higher fault-tolerant capability than other gamma networks at low cost. Terminal pair reliabilities of proposed designs and various other 2-disjoint and 3-disjoint GINs are evaluated, analyzed and compared. Reliability values of proposed designs are found higher.     

On Short Paths Interdiction Problems: Total and Node-Wise Limited Interdiction

Given a directed graph G=(V,A) with a non-negative weight (length) function on its arcs w:A→ℝ₊ and two terminals s,t∈V, our goal is to destroy all short directed paths from s to t in G by eliminating some arcs of A. This is known as the short paths interdiction problem. We consider several versions of it, and in each case analyze two subcases: total limited interdiction, when a fixed number k of arcs can be removed, and node-wise limited interdiction, when for each node v∈V a fixed number k(v) of out-going arcs can be removed. Our results indicate that the latter subcase is always easier than the former one. In particular, we show that the short paths node-wise interdiction problem can be efficiently solved by an extension of Dijkstra’s algorithm. In contrast, the short paths total interdiction problem is known to be NP-hard. We strengthen this hardness result by deriving the following inapproximability bounds: Given k, it is NP-hard to approximate within a factor c<2 the maximum s–t distance d(s,t) obtainable by removing (at most) k arcs from G. Furthermore, given d, it is NP-hard to approximate within a factor the minimum number of arcs which has to be removed to guarantee d(s,t)≥d. Finally, we also show that the same inapproximability bounds hold for undirected graphs and/or node elimination. This research was supported in part by NSF grant IIS-0118635 and by DIMACS, the NSF Center for Discrete Mathematics & Theoretical Computer Science. Preprints DTR-2005-04 and DTR-2006-13 are available at and . Our co-author Leonid Khachiyan passed away with tragic suddenness on April 29th, 2005.     

The super-connected property of recursive circulant graphs

In a graph G, a k-container C_k(u,v) is a set of k disjoint paths joining u and v. A k-container C_k(u,v) is k∗-container if every vertex of G is passed by some path in C_k(u,v). A graph G is k∗-connected if there exists a k∗-container between any two vertices. An m-regular graph G is super-connected if G is k∗-connected for any k with 1?k?m. In this paper, we prove that the recursive circulant graphs G(2^m,4), proposed by Park and Chwa [Theoret. Comput. Sci. 244 (2000) 35-62], are super-connected if and only if m≠2.     

A linear algorithm for the all-bidirectional-edges problem on planar graphs

The all-bidirectional-edges problem is to find an edge-labeling of an undirected networkG=(V, E), with a source and a sink, such that an edgee=uv inE is labeled u, v or u, u (or both) depending on the existence of a (simple) path from the source to the sink traversinge, that visits the verticesu andv in the orderu, v orv, u respectively. The best-known algorithm for this problem requiresO(¦V¦·¦E¦) time [5]. We show that the problem is solvable optimally on a planar graph.     

Maximum <Emphasis Type="Italic">k</Emphasis>-Splittable <Emphasis Type="Italic">s</Emphasis>,<Emphasis Type="Italic">t</Emphasis>-Flows

Given a graph with a source and a sink node, the NP-hard maximum k-splittable s,t-flow (M k SF) problem is to find a flow of maximum value from s to t with a flow decomposition using at most k paths. The multicommodity variant of this problem is a natural generalization of disjoint paths and unsplittable flow problems. Constructing a k-splittable flow requires two interdepending decisions. One has to decide on k paths (routing) and on the flow values for the paths (packing). We give efficient algorithms for computing exact and approximate solutions by decoupling the two decisions into a first packing step and a second routing step. Usually the routing is considered before the packing. Our main contributions are as follows: (i) We show that for constant k a polynomial number of packing alternatives containing at least one packing used by an optimal M k SF solution can be constructed in polynomial time. If k is part of the input, we obtain a slightly weaker result. In this case we can guarantee that, for any fixed ε>0, the computed set of alternatives contains a packing used by a (1−ε)-approximate solution. The latter result is based on the observation that (1−ε)-approximate flows only require constantly many different flow values. We believe that this observation is of interest in its own right. (ii) Based on (i), we prove that, for constant k, the M k SF problem can be solved in polynomial time on graphs of bounded treewidth. If k is part of the input, this problem is still NP-hard and we present a polynomial time approximation scheme for it.     

Improved algorithms for finding length-bounded two vertex-disjoint paths in a planar graph and minmax k vertex-disjoint paths in a directed acyclic graph

This paper is composed of two parts. In the first part, an improved algorithm is presented for the problem of finding length-bounded two vertex-disjoint paths in an undirected planar graph. The presented algorithm requires O(n³bmin) time and O(n²bmin) space, where bmin is the smaller of the two given length bounds. In the second part of this paper, we consider the minmax k vertex-disjoint paths problem on a directed acyclic graph, where k?2 is a constant. An improved algorithm and a faster approximation scheme are presented. The presented algorithm requires O(nk+1Mk−1) time and O(nkMk−1) space, and the presented approximation scheme requires O((1/?)^k−1n2klogk−1M) time and O((1/?)^k−1n2k−1logk−1M) space, where ? is the given approximation parameter and M is the length of the longest path in an optimal solution.     

Bidirectional edges problem: Part I—A simple algorithm

The bidirectional edges problem is to find an edge-labeling of an undirected network,G=(V, E), with a source and a sink, such that an edge [u, v] E is labeled (u, v) or (v, u) (or both) depending on the existence of a (simple) path from the source to sink that visits the verticesu andv, in the orderu, v orv, u, respectively. We provide several algorithms for this problem in the current paper and the sequel. In this paper we show the relation between this problem and the classical two-vertex-disjoint-paths problem and then devise a simple algorithm with a time complexity ofO(|E|·|V|²). In the sequel we improve the time complexity toO(|E|·|V|). The main technique exploits aclever partition of the graph into a set of paths and bridges which are then analyzed recursively.The bidirectional edges problem arises naturally in the context of the simulation of an MOS transistor network, in which a transistor may operate as a unilateral or a bilateral device, depending on the voltages at its source and drain nodes. For efficient simulation, it is required to detect the set of transistors that may operate as bilateral devices. Also, sometimes it is intended to propagate information in one direction only, and propagation in the wrong direction (resulting in asneak path) can cause functional error. Our algorithms can be used to detect all the sneak paths.This research was supported in part by National Science Foundation Grants DMS-8703458 and CCR-9002819.     

A 2-approximation algorithm for the vertex cover P4 problem in cubic graphs

A subset F of vertices of a graph G is called a vertex cover P_k set if every path of order k in G contains at least one vertex from F. Denote by ψ_k(G) the minimum cardinality of a vertex cover P_k set in G. The vertex cover P_k (VCP_k) problem is to find a minimum vertex cover P_k set. It is easy to see that the VCP₂ problem corresponds to the well-known vertex cover problem. In this paper, we restrict our attention to the VCP₄ problem in cubic graphs. The paper proves that the VCP₄ problem is NP-hard for cubic graphs. Further, we give sharp lower and upper bounds on ψ₄(G) for cubic graphs and propose a 2-approximation algorithm for the VCP₄ problem in cubic graphs.     

Transmission reliability of k minimal paths within time threshold

The quickest path problem involving two attributes, the capacity and the lead time, is to find a single path with minimum transmission time. The capacity of each arc is assumed to be deterministic in this problem. However, in many practical networks such as computer networks, telecommunication networks, and logistics networks, each arc is multistate due to failure, maintenance, etc. Such a network is named a multistate flow network. Hence, both the transmission time to deliver data through a minimal path and the minimum transmission time through a multistate flow network are not fixed. In order to reduce the transmission time, the data can be transmitted through k minimal paths simultaneously. The purpose of this paper is to evaluate the probability that d units of data can be transmitted through k minimal paths within time threshold T. Such a probability is called the transmission reliability. A simple algorithm is proposed to generate all lower boundary points for (d, T), the minimal system states satisfying the demand within time threshold. The transmission reliability can be subsequently computed in terms of such points. Another algorithm is further proposed to find the optimal combination of k minimal paths with highest transmission reliability.     

Path-matching problems

The notion of matching in graphs is generalized in this paper to a set of paths rather than to a set of edges. The generalized problem, which we call thepath-matching problem, is to pair the vertices of an undirected weighted graph such that the paths connecting each pair are subject to certain objectives and/or constraints. This paper concentrates on the case where the paths are required to be edge-disjoint and the objective is to minimize the maximal cost of a path in the matching (i.e., the bottleneck version). Other variations of the problem are also mentioned. Two algorithms are presented to find the best matching under the constraints listed above for trees. Their worst-case running times areO(n logd logw), whered is the maximal degree of a vertex,w is the maximal cost of an edge, andn is the size of the tree, andO(n ²), respectively. The problem is shown to be NP-complete for general graphs. Applications of these problems are also discussed.Udi Manber was supported in part by an NSF Presidential Young Investigator Award (Grant DCR-8451397), with matching funds from AT&T.     

On Rooted Node-Connectivity Problems

Let G be a graph which is k -outconnected from a specified root node r , that is, G has k openly disjoint paths between r and v for every node v . We give necessary and sufficient conditions for the existence of a pair rv,rw of edges for which replacing these edges by a new edge vw gives a graph that is k -outconnected from r . This generalizes a theorem of Bienstock et al. on splitting off edges while preserving k -node-connectivity. We also prove that if C is a cycle in G such that each edge in C is critical with respect to k -outconnectivity from r , then C has a node v , distinct from r , which has degree k . This result is the rooted counterpart of a theorem due to Mader. We apply the above results to design approximation algorithms for the following problem: given a graph with nonnegative edge weights and node requirements c _u for each node u , find a minimum-weight subgraph that contains max {c _u ,c _v } openly disjoint paths between every pair of nodes u,v . For metric weights, our approximation guarantee is 3 . For uniform weights, our approximation guarantee is \min{ 2, (k+2q-1)/k} . Here k is the maximum node requirement, and q is the number of positive node requirements. Received September 15, 1998; revised March 10, 2000, and April 17, 2000.     

Fault-tolerant routing over shortest node-disjoint paths in hypercubes

This paper presented a routing algorithm that finds n disjoint shortest paths from the source node s to target node d in the n-dimensional hypercube. Fault-tolerant routing over all shortest node-disjoint paths has been investigated to overcome the failure encountered during routing in hypercube networks. In this paper, we proposed an efficient approach to provide fault-tolerant routing which has been investigated on hypercube networks. The proposed approach is based on all shortest node-disjoint paths concept in order to find a fault-free shortest path among several paths provided. The proposed algorithm is a simple uniform distributed algorithm that can tolerate a large number of process failures, while delivering all n messages over optimal-length disjoint paths. However, no distributed algorithm uses acknowledgement messages (acks) for fault tolerance. So, for dealing the faults, acknowledgement messages (acks) are included in the proposed algorithm for routing messages over node-disjoint paths in a hypercube network.     

A Fan-type result on k-ordered graphs

For a positive integer k, a graph G is k-ordered hamiltonian if for every ordered sequence of k vertices there is a hamiltonian cycle that encounters the vertices of the sequence in the given order. In this paper, we show that if G is a ⌊3k/2⌋-connected graph of order n?100k, and d(u)+d(v)?n for any two vertices u and v with d(u,v)=2, then G is k-ordered hamiltonian. Our result implies the theorem of G. Chen et al. [Ars Combin. 70 (2004) 245-255] [1], which requires the degree sum condition for all pairs of non-adjacent vertices, not just those distance 2 apart.     

On Clark and Suen bound-type results for k-domination and Roman domination of Cartesian product graphs

A set S of vertices of a graph G is a dominating set for G if every vertex of G is adjacent to at least one vertex of S. The domination number γ(G), of G, is the minimum cardinality of a dominating set in G. Moreover, if the maximum degree of G is Δ, then for every positive integer k≤Δ, the set S is a k-dominating set in G if every vertex outside of S is adjacent to at least k vertices of S. The k-domination number of G, denoted by γ _k (G), is the minimum cardinality of a k-dominating set in G. A map f: V→<texlscub>0, 1, 2</texlscub>is a Roman dominating function for G if for every vertex v with f(v)=0, there exists a vertex u∈N(v) such that f(u)=2. The weight of a Roman dominating function is f(V)=∑ _u∈V f(u). The Roman domination number γ_R(G), of G, is the minimum weight of a Roman dominating function on G. In this paper, we obtain that for any two graphs G and H, the k-domination number of the Cartesian product of G and H is bounded below by γ(G)γ _k (H)/2. Also, we obtain that the domination number of Cartesian product of G and H is bounded below by γ(G)γ_R(H)/3.