Graph Searching, Elimination Trees, and a Generalization of Bandwidth

The bandwidth minimization problem has a long history and a number of practical applications. In this paper we introduce a natural extension of bandwidth to partially ordered layouts. We consider this extension from three main viewpoints: graph searching, tree decompositions, and elimination orderings. The three graph parameters pathwidth, profile, and bandwidth related to linear layouts can be defined by variants of graph searching using a standard fugitive. Switching to an inert fugitive, the two former parameters are extended to treewidth and fill-in, and our first viewpoint considers the analogous tree-like extension that arises from the bandwidth variant. Bandwidth also has a definition in terms of ordered path decompositions, and our second viewpoint extends this in a natural way to ordered tree decompositions. In showing that both extensions are equivalent we employ the third viewpoint of elimination trees, as used in the field of sparse matrix computations. We call the resulting parameter the treespan of a graph and prove some of its combinatorial and algorithmic properties.     

Graph Searching, Elimination Trees, and a Generalization of Bandwidth

The bandwidth minimization problem has a long history and a number of practical applications. In this paper we introduce a natural extension of bandwidth to partially ordered layouts. We consider this extension from three main viewpoints: graph searching, tree decompositions, and elimination orderings. The three graph parameters pathwidth, profile, and bandwidth related to linear layouts can be defined by variants of graph searching using a standard fugitive. Switching to an inert fugitive, the two former parameters are extended to treewidth and fill-in, and our first viewpoint considers the analogous tree-like extension that arises from the bandwidth variant. Bandwidth also has a definition in terms of ordered path decompositions, and our second viewpoint extends this in a natural way to ordered tree decompositions. In showing that both extensions are equivalent we employ the third viewpoint of elimination trees, as used in the field of sparse matrix computations. We call the resulting parameter the treespan of a graph and prove some of its combinatorial and algorithmic properties.     

Linear Time Solvable Optimization Problems on Graphs of Bounded Clique-Width

Hierarchical decompositions of graphs are interesting for algorithmic purposes. There are several types of hierarchical decompositions. Tree decompositions are the best known ones. On graphs of tree-width at most k , i.e., that have tree decompositions of width at most k , where k is fixed, every decision or optimization problem expressible in monadic second-order logic has a linear algorithm. We prove that this is also the case for graphs of clique-width at most k , where this complexity measure is associated with hierarchical decompositions of another type, and where logical formulas are no longer allowed to use edge set quantifications. We develop applications to several classes of graphs that include cographs and are, like cographs, defined by forbidding subgraphs with ``too many' induced paths with four vertices. Received April 13, 1998, and in revised form June 22, 1999, and in final form August 20, 1999.     

How to Guard a Graph?

We initiate the study of the algorithmic foundations of games in which a set of cops has to guard a region in a graph (or digraph) against a robber. The robber and the cops are placed on vertices of the graph; they take turns in moving to adjacent vertices (or staying). The goal of the robber is to enter the guarded region at a vertex with no cop on it. The problem is to find the minimum number of cops needed to prevent the robber from entering the guarded region. The problem is highly non-trivial even if the robber’s or the cops’ regions are restricted to very simple graphs. The computational complexity of the problem depends heavily on the chosen restriction. In particular, if the robber’s region is only a path, then the problem can be solved in polynomial time. When the robber moves in a tree (or even in a star), then the decision version of the problem is NP-complete. Furthermore, if the robber is moving in a directed acyclic graph, the problem becomes PSPACE-complete.     

Digraph measures: Kelly decompositions, games, and orderings

We consider various well-known, equivalent complexity measures for graphs such as elimination orderings, k$k$-trees and cops and robber games and study their natural translations to digraphs. We show that on digraphs the translations of these measures are also equivalent and induce a natural connectivity measure. We introduce a decomposition for digraphs and an associated width, Kelly-width, which is equivalent to the aforementioned measure. We demonstrate its usefulness by exhibiting potential applications including polynomial-time algorithms for NP-complete problems on graphs of bounded Kelly-width, and complexity analysis of asymmetric matrix factorization. Finally, we compare the new width to other known decompositions of digraphs.     

Parameterized complexity of the induced subgraph problem in directed graphs

In this Letter, we consider the parameterized complexity of the following problem: Given a hereditary property P on digraphs, an input digraph D and a positive integer k, does D have an induced subdigraph on k vertices with property P? We completely characterize hereditary properties for which this induced subgraph problem is W[1]-complete for two classes of directed graphs: general directed graphs and oriented graphs. We also characterize those properties for which the induced subgraph problem is W[1]-complete for general directed graphs but fixed parameter tractable for oriented graphs. These results are among the very few parameterized complexity results on directed graphs.     

Monotony properties of connected visible graph searching

Search games are attractive for their correspondence with classical width parameters. For instance, the invisible search number (a.k.a. node search number) of a graph is equal to its pathwidth plus 1, and the visible search number of a graph is equal to its treewidth plus 1. The connected variants of these games ask for search strategies that are connected, i.e., at every step of the strategy, the searched part of the graph induces a connected subgraph. We focus on monotone search strategies, i.e., strategies for which every node is searched exactly once. The monotone connected visible search number of an n-node graph is at most O(logn) times its visible search number. First, we prove that this logarithmic bound is tight. Precisely, we prove that there is an infinite family of graphs for which the ratio monotone connected visible search number over visible search number is Ω(logn). Second, we prove that, as opposed to the non-connected variant of visible graph searching, “recontamination helps” for connected visible search. Precisely, we prove that, for any k4, there exists a graph with connected visible search number at most k, and monotone connected visible search number >k     

Tradeoffs in process strategy games with application in the WDM reconfiguration problem

We consider a variant of the graph searching games that models the routing reconfiguration problem in WDM networks. In the digraph processing game, a team of agents aims at processing, or clearing, the vertices of a digraph D. We are interested in two different measures: (1) the total number of agents used, and (2) the total number of vertices occupied by an agent during the processing of D. These measures, respectively, correspond to the maximum number of simultaneous connections interrupted and to the total number of interruptions during a routing reconfiguration in a WDM network.Previous works have studied the problem of independently minimizing each of these parameters. In particular, the corresponding minimization problems are APX-hard, and the first one is known not to be in APX. In this paper, we give several complexity results and study tradeoffs between these conflicting objectives. In particular, we show that minimizing one of these parameters while the other is constrained is NP-complete. Then, we prove that there exist some digraphs for which minimizing one of these objectives arbitrarily impairs the quality of the solution for the other one. We show that such bad tradeoffs may happen even for a basic class of digraphs. On the other hand, we exhibit classes of graphs for which good tradeoffs can be achieved. We finally detail the relationship between this game and the routing reconfiguration problem. In particular, we prove that any instance of the processing game, i.e. any digraph, corresponds to an instance of the routing reconfiguration problem.     

A browser for directed graphs

A general-purpose browser for directed graphs is described. The browser provides operations to examine and edit graphs and to generate a layout for a graph automatically that minimizes edge crossings. Two layout algorithms were implemented. A hierarchical graph layout algorithm was found to be best for directed graphs. The graph browser also has facilities that allow it to be integrated with other applications (e.g. a program browser). These facilities and our experiences building a program call-graph browser are described.     

An Extended Tree-Width Notion for Directed Graphs Related to the Computation of Permanents

It is well known that permanents of matrices of bounded tree-width are efficiently computable. Here, the tree-width of a square matrix M=(m _ij ) with entries from a field \(\mathbb{K}\) is the tree-width of the underlying graph G _M having an edge (i,j) if and only if the entry m _ij ≠0. Though G _M is directed this does not influence the tree-width definition. Thus, it does not reflect the lacking symmetry when m _ij ≠0 but m _ji =0. The latter however might have impact on the computation of the permanent. In this paper we introduce and study an extended notion of tree-width for directed graphs called triangular tree-width. We give examples where the latter parameter is bounded whereas the former is not. As main result we show that permanents of matrices of bounded triangular tree-width are efficiently computable. This result is shown to hold as well for the Hamiltonian Cycle problem.     

Approximating the max-edge-coloring problem

The max-edge-coloring problem is a natural weighted generalization of the classical edge-coloring problem arising in the domain of communication systems. In this problem each color class is assigned the weight of the heaviest edge in this class and the objective is to find a proper edge-coloring of the input graph minimizing the sum of all color classes’ weights. We present new approximation results, that improve substantially the known ones, for several variants of the problem with respect to the class of the underlying graph. In particular, we deal with variants which are known to be NP-hard (general and bipartite graphs) or are proven to be NP-hard in this paper (complete graphs with bi-valued edge weights) or whose complexity question still remains open (trees).     

k-tuple domination in graphs

In a graph G, a vertex is said to dominate itself and all of its neighbors. For a fixed positive integer k, the k-tuple domination problem is to find a minimum sized vertex subset in a graph such that every vertex in the graph is dominated by at least k vertices in this set. The current paper studies k-tuple domination in graphs from an algorithmic point of view. In particular, we give a linear-time algorithm for the k-tuple domination problem in strongly chordal graphs, which is a subclass of chordal graphs and includes trees, block graphs, interval graphs and directed path graphs. We also prove that the k-tuple domination problem is NP-complete for split graphs (a subclass of chordal graphs) and for bipartite graphs.     

Editing to Eulerian graphs

The Eulerian Editing problem asks, given a graph G and an integer k, whether G can be modified into an Eulerian graph using at most k edge additions and edge deletions. We show that this problem is polynomial-time solvable for both undirected and directed graphs. We generalize these results for problems with degree parity constraints and degree balance constraints, respectively. We also consider the variants where vertex deletions are permitted. Combined with known results, this leads to full complexity classifications for both undirected and directed graphs and for every subset of the three graph operations.     

AND/OR search spaces for graphical models

The paper introduces an AND/OR search space perspective for graphical models that include probabilistic networks (directed or undirected) and constraint networks. In contrast to the traditional (OR) search space view, the AND/OR search tree displays some of the independencies present in the graphical model explicitly and may sometimes reduce the search space exponentially. Indeed, most algorithmic advances in search-based constraint processing and probabilistic inference can be viewed as searching an AND/OR search tree or graph. Familiar parameters such as the depth of a spanning tree, treewidth and pathwidth are shown to play a key role in characterizing the effect of AND/OR search graphs vs. the traditional OR search graphs. We compare memory intensive AND/OR graph search with inference methods, and place various existing algorithms within the AND/OR search space.     

Combinatorial algorithms for feedback problems in directed graphs

Given a weighted directed graph G=(V,A), the minimum feedback arc set problem consists of finding a minimum weight set of arcs A′⊆A such that the directed graph (V,A?A′) is acyclic. Similarly, the minimum feedback vertex set problem consists of finding a minimum weight set of vertices containing at least one vertex for each directed cycle. Both problems are NP-complete. We present simple combinatorial algorithms for these problems that achieve an approximation ratio bounded by the length, in terms of number of arcs, of a longest simple cycle of the digraph.     

Using graph parsing for automatic graph drawing

This paper presents a procedure for automatically drawing directed graphs. Our system, Clan-based Graph Drawing Tool (CG), uses a unique clan-based graph decomposition to determine intrinsic substructures (clans) in the graph and to produce a parse tree. The tree is given attributes that specify the node layout. CG then uses tree properties with the addition of “routing nodes” to route the edges. The objective of the system is to provide, automatically, an aesthetically pleasing visual layout for arbitrary directed graphs. The prototype has shown the strengths of this approach. The innovative strategy of clan-based graph decomposition is the first digraph drawing technique to analyze locality in the graph in two dimensions. The typical approach to drawing digraphs uses a single dimension, level, to arrange the nodes     

Monotonicity of non-deterministic graph searching

In graph searching, a team of searchers are aiming at capturing a fugitive moving in a graph. In the initial variant, called invisible graph searching, the searchers do not know the position of the fugitive until they catch it. In another variant, the searchers permanently know the position of the fugitive, i.e. the fugitive is visible. This latter variant is called visible graph searching. A search strategy that catches any fugitive in such a way that the part of the graph reachable by the fugitive never grows is called monotone. A priori, monotone strategies may require more searchers than general strategies to catch any fugitive. This is however not the case for visible and invisible graph searching. Two important consequences of the monotonicity of visible and invisible graph searching are: (1) the decision problem corresponding to the computation of the smallest number of searchers required to clear a graph is in NP, and (2) computing optimal search strategies is simplified by taking into account that there exist some that never backtrack.

Fomin et al. [F.V. Fomin, P. Fraigniaud, N. Nisse, Nondeterministic graph searching: From pathwidth to treewidth, in: Proceedings of the 30th International Symposium on Mathematical Foundations of Computer Science, MFCS’05, 2005, pp. 364–375] introduced an important graph searching variant, called non-deterministic graph searching, that unifies visible and invisible graph searching. In this variant, the fugitive is invisible, and the searchers can query an oracle that permanently knows the current position of the fugitive. The question of the monotonicity of non-deterministic graph searching was however left open.

In this paper, we prove that non-deterministic graph searching is monotone. In particular, this result is a unified proof of monotonicity for visible and invisible graph searching. As a consequence, the decision problem corresponding to non-deterministic graph searching belongs to NP. Moreover, the exact algorithms designed by Fomin et al. do compute optimal non-deterministic search strategies.     

Applications of graph theory in computer systems

Many problem situations in computer systems can be analyzed using models based on directed graphs. The vertices of the graph represent states of the system and the directed arcs represent the transitions between these states. This paper is in two parts. The first introduces the concepts of directed graphs and their representations in computers and presents some basic problems and algorithms. The second part examines the application of graph theory to various areas of computer systems.