Graphs In Linear Time Research Articles

Search Numbers in Networks with Special Topologies

In this paper, we consider the problem of finding the minimum number of searchers to sweep networks/graphs with special topological structures. Such a number is called the search number. We first study graphs, which contain only one cycle, and present a linear time algorithm to compute the vertex separation and the optimal layout of such graphs; by a linear-time transformation, we can find the search number of this kind of graphs in linear time. We also investigate graphs, in which every vertex lies on at most one cycle and each cycle contains at most three vertices of degree more than two, and we propose a linear time algorithm to compute their search number and optimal search strategy. We prove explicit formulas for the search number of the graphs obtained from complete k-ary trees by replacing vertices by cycles. We also present some results on approximation algorithms.

Integer programming approach to static monopolies in graphs

A subset M of vertices of a graph is called a static monopoly, if any vertex v outside M has at least $$\lceil \tfrac{1 }{2}\deg (v)\rceil $$ neighbors in M. The minimum static monopoly problem has been extensively studied in graph theoretical context. We study this problem from an integer programming point of view for the first time and give a linear formulation for it. We study the facial structure of the corresponding polytope, classify facet defining inequalities of the integer programming formulation and introduce some families of valid inequalities. We show that in the presence of a vertex cut or an edge cut in the graph, the problem can be solved more efficiently by adding some strong valid inequalities. An algorithm is given that solves the minimum monopoly problem in trees and cactus graphs in linear time. We test our methods by performing several experiments on randomly generated graphs. A software package is introduced that solves the minimum monopoly problem using open source integer linear programming solvers.

On the maximum forcing and anti-forcing numbers of [formula omitted]-fullerenes

Let G be a (4,6)-fullerene graph. We show that the maximum forcing number of G is equal to its Clar number, and the maximum anti-forcing number of G is equal to its Fries number, which extend the known results for hexagonal systems with a perfect matching (Xu et al., 2013; Lei et al., 2016). Moreover, we obtain two formulas dependent only on the order of G to count the Clar number and Fries number of G respectively. Hence we can compute the maximum forcing number of a (4,6)-fullerene graph in linear time. This answers an open problem proposed by Afshani et al. (2004) in the case of (4,6)-fullerene graphs.

Computing the clique-separator graph for an interval graph in linear time

We present an algorithm to compute the clique-separator graph of an interval graph in O(m+n) time. This improves the running time of O(n2) given in [11]. The algorithm is simple and uses no complicated data structures.

Linear Time Algorithms to Restrict Insider Access using Multi-Policy Access Control Systems.

An important way to limit malicious insiders from distributing sensitive information is to as tightly as possible limit their access to information. This has always been the goal of access control mechanisms, but individual approaches have been shown to be inadequate. Ensemble approaches of multiple methods instantiated simultaneously have been shown to more tightly restrict access, but approaches to do so have had limited scalability (resulting in exponential calculations in some cases). In this work, we take the Next Generation Access Control (NGAC) approach standardized by the American National Standards Institute (ANSI) and demonstrate its scalability. The existing publicly available reference implementations all use cubic algorithms and thus NGAC was widely viewed as not scalable. The primary NGAC reference implementation took, for example, several minutes to simply display the set of files accessible to a user on a moderately sized system. In our approach, we take these cubic algorithms and make them linear. We do this by reformulating the set theoretic approach of the NGAC standard into a graph theoretic approach and then apply standard graph algorithms. We thus can answer important access control decision questions (e.g., which files are available to a user and which users can access a file) using linear time graph algorithms. We also provide a default linear time mechanism to visualize and review user access rights for an ensemble of access control mechanisms. Our visualization appears to be a simple file directory hierarchy but in reality is an automatically generated structure abstracted from the underlying access control graph that works with any set of simultaneously instantiated access control policies. It also provide an implicit mechanism for symbolic linking that provides a powerful access capability. Our work thus provides the first efficient implementation of NGAC while enabling user privilege review through a novel visualization approach. This may help transition from concept to reality the idea of using ensembles of simultaneously instantiated access control methodologies, thereby limiting insider threat.

Using SPQR-trees to speed up recognition algorithms based on 2-cutsets

Several well-studied classes of graphs admit structural characterizations via proper 2-cutsets which lead to polynomial-time recognition algorithms. The algorithms so far obtained for those recognition problems do not guarantee linear-time complexity. The bottleneck to those algorithms is the Ω(nm)-time complexity to fully decompose by proper 2-cutsets a graph with n vertices and m edges. In the present work, we investigate the 3-connected components of a graph and propose the use of the SPQR-tree data structure to obtain a fully decomposed graph in linear time. As a consequence, we show that the recognition of chordless graphs and of graphs that do not contain a propeller as a subgraph can be done in linear time, answering questions in the existing literature.

Recognizing Optimal 1-Planar Graphs in Linear Time

A graph with n vertices is 1-planar if it can be drawn in the plane such that each edge is crossed at most once, and is optimal if it has the maximum of 4n-8 edges. We show that optimal 1-planar graphs can be recognized in linear time. Our algorithm implements a graph reduction system with two rules, which can be used to reduce every optimal 1-planar graph to an irreducible extended wheel graph. The graph reduction system is non-deterministic, constraint, and non-confluent.

2-Edge Connectivity in Directed Graphs

Edge and vertex connectivity are fundamental concepts in graph theory. While they have been thoroughly studied in the case of undirected graphs, surprisingly, not much has been investigated for directed graphs. In this article, we study 2-edge connectivity problems in directed graphs and, in particular, we consider the computation of the following natural relation: We say that two vertices v and w are 2- edge-connected if there are two edge-disjoint paths from v to w and two edge-disjoint paths from w to v . This relation partitions the vertices into blocks such that all vertices in the same block are 2-edge-connected. Differently from the undirected case, those blocks do not correspond to the 2-edge-connected components of the graph. The main result of this article is an algorithm for computing the 2-edge-connected blocks of a directed graph in linear time. Besides being asymptotically optimal, our algorithm improves significantly over previous bounds. Once the 2-edge-connected blocks are available, we can test in constant time if two vertices are 2-edge-connected. Additionally, when two query vertices v and w are not 2-edge-connected, we can produce in constant time a “witness” of this property by exhibiting an edge that is contained in all paths from v to w or in all paths from w to v . We are also able to compute in linear time a sparse certificate for this relation, i.e., a subgraph of the input graph that has O ( n ) edges and maintains the same 2-edge-connected blocks as the input graph, where n is the number of vertices.

Linear recognition of generalized Fibonacci cubes $Q_h(111)$

The generalized Fibonacci cube $Q_h(f)$ is the graph obtained from the $h$-cube $Q_h$ by removing all vertices that contain a given binary string $f$ as a substring. In particular, the vertex set of the 3rd order generalized Fibonacci cube $Q_h(111)$ is the set of all binary strings $b_1b_2 \ldots b_h$ containing no three consecutive 1's. We present a new characterization of the 3rd order generalized Fibonacci cubes based on their recursive structure. The characterization is the basis for an algorithm which recognizes these graphs in linear time.

Approximate tree decompositions of planar graphs in linear time

Many algorithms have been developed for NP-hard problems on graphs with small treewidth k. For example, all problems that are expressible in linear extended monadic second order can be solved in linear time on graphs of bounded treewidth. It turns out that the bottleneck of many algorithms for NP-hard problems is the computation of a tree decomposition of width O(k). In particular, by the bidimensional theory, there are many linear extended monadic second order problems that can be solved on n-vertex planar graphs with treewidth k in a time linear in n and subexponential in k if a tree decomposition of width O(k) can be found in such a time.We present the first algorithm that, on n-vertex planar graphs with treewidth k, finds a tree decomposition of width O(k) in such a time. In more detail, our algorithm has a running time of O(nk2log⁡k). We show the result as a special case of a result concerning so-called weighted treewidth of weighted graphs.

Induced disjoint paths in circular-arc graphs in linear time

The Induced Disjoint Paths problem is to test whether an graph G on n vertices with k distinct pairs of vertices (si,ti) contains paths P1,…,Pk such that Pi connects si and ti for i=1,…,k, and Pi and Pj have neither common vertices nor adjacent vertices (except perhaps their ends) for 1≤i<j≤k. We present a linear-time algorithm that solves Induced Disjoint Paths and finds the corresponding paths (if they exist) on circular-arc graphs. For interval graphs, we exhibit a linear-time algorithm for the generalization of Induced Disjoint Paths where the pairs (si,ti) are not necessarily distinct. In both cases, if a representation of the graph is given, then the algorithms run in O(n+k) time.

Simple Recognition of Halin Graphs and Their Generalizations

We describe and implement two local reduction rules that can be used to recognize Halin graphs in linear time, avoiding the complicated planarity testing step of previous linear time Halin graph recognition algorithms. The same two rules can be used as the basis for linear-time algorithms for other algorithmic problems on Halin graphs, including decomposing these graphs into a tree and a cycle, finding a Hamiltonian cycle, or constructing a planar embedding. These reduction rules can also be used to recognize a broader class of polyhedral graphs. These graphs, which we call the D3-reducible graphs, are the dual graphs of the polyhedra formed by gluing pyramids together on their triangular faces; their treewidth is bounded, and they necessarily have Lombardi drawings.

A linear time algorithm to compute a maximum weighted independent set on cocomparability graphs

The maximum weight independent set (WMIS) problem is a well-known NP-hard problem. It is a generalization of the maximum cardinality independent set problem where all the vertices have identical weights. There is an O(n2) time algorithm to compute a WMIS for cocomparability graphs by computing a maximum weight clique on the corresponding complement of the graph [1]. We present the first O(m+n) time algorithm to compute a WMIS directly on the given cocomparability graph, where m and n are the number of edges and vertices of the graph respectively. As a corollary, we get the minimum weight vertex cover of a cocomparability graph in linear time as well.

Ramified Rectilinear Polygons: Coordinatization by Dendrons

Simple rectilinear polygons (i.e. rectilinear polygons without holes or cutpoints) can be regarded as finite rectangular cell complexes coordinatized by two finite dendrons. The intrinsic $l_1$-metric is thus inherited from the product of the two finite dendrons via an isometric embedding. The rectangular cell complexes that share this same embedding property are called ramified rectilinear polygons. The links of vertices in these cell complexes may be arbitrary bipartite graphs, in contrast to simple rectilinear polygons where the links of points are either 4-cycles or paths of length at most 3. Ramified rectilinear polygons are particular instances of rectangular complexes obtained from cube-free median graphs, or equivalently simply connected rectangular complexes with triangle-free links. The underlying graphs of finite ramified rectilinear polygons can be recognized among graphs in linear time by a Lexicographic Breadth-First-Search. Whereas the symmetry of a simple rectilinear polygon is very restricted (with automorphism group being a subgroup of the dihedral group $D_4$), ramified rectilinear polygons are universal: every finite group is the automorphism group of some ramified rectilinear polygon.

Finding outer-connected dominating sets in interval graphs

An outer-connected dominating set in a graph G=(V,E) is a set S⊆V such that each vertex not in S is adjacent to at least one vertex in S and the subgraph induced by V∖S is connected. In Keil and Pradhan (2013) [6], Keil and Pradhan gave a linear-time algorithm for finding a minimum outer-connected dominating set in a proper interval graph. In this paper, we generalize their result to find a minimum outer-connected dominating set in an interval graph in linear time.

Rainbow colouring of split graphs

A rainbow path in an edge coloured graph is a path in which no two edges are coloured the same. A rainbow colouring of a connected graph G is a colouring of the edges of G such that every pair of vertices in G is connected by at least one rainbow path. The minimum number of colours required to rainbow colour G is called its rainbow connection number. It is known that, unless P=NP, the rainbow connection number of a graph cannot be approximated in polynomial time to a multiplicative factor less than 5/4, even when the input graph is chordal [Chandran and Rajendraprasad, FSTTCS 2013]. In this article, we determine the computational complexity of the above problem on successively more restricted graph classes, viz.: split graphs and threshold graphs. In particular, we establish the following:1.The problem of deciding whether a given split graph can be rainbow coloured using k colours is NP-complete for k∈{2,3}, but can be solved in polynomial time for all other values of k. Furthermore, any split graph can be rainbow coloured in linear time using at most one more colour than the optimum.2.For every positive integer k, threshold graphs with rainbow connection number k can be characterised based on their degree sequence alone. Furthermore, we can optimally rainbow colour a threshold graph in linear time.

Fast recognition of partial star products and quasi cartesian products

This paper is concerned with the fast computation of a relation d on the edge set of connected graphs that plays a decisive role in the recognition of approximate Cartesian products, the weak reconstruction of Cartesian products, and the recognition of Cartesian graph bundles with a triangle free basis. A special case of d is the relation δ * , whose convex closure yields the product relation σ that induces the prime factor decomposition of connected graphs with respect to the Cartesian product. For the construction of d so-called Partial Star Products are of particular interest. Several special data structures are used that allow to compute Partial Star Products in constant time. These computations are tuned to the recognition of approximate graph products, but also lead to a linear time algorithm for the computation of δ * for graphs with maximum bounded degree. Furthermore, we define quasi Cartesian products as graphs with non-trivial δ * . We provide several examples, and show that quasi Cartesian products can be recognized in linear time for graphs with bounded maximum degree. Finally, we note that quasi products can be recognized in sublinear time with a parallelized algorithm.

A 2-dimensional optical architecture for solving Hamiltonian path problem based on micro ring resonators

Abstract The problem of finding the Hamiltonian path in a graph, or deciding whether a graph has a Hamiltonian path or not, is an NP-complete problem. No exact solution has been found yet, to solve this problem using polynomial amount of time and space. In this paper, we propose a two dimensional (2-D) optical architecture based on optical electronic devices such as micro ring resonators, optical circulators and MEMS based mirror (MEMS-M) to solve the Hamiltonian Path Problem, for undirected graphs in linear time. It uses a heuristic algorithm and employs n +1 different wavelengths of a light ray, to check whether a Hamiltonian path exists or not on a graph with n vertices. Then if a Hamiltonian path exists, it reports the path. The device complexity of the proposed architecture is O( n 2 ).

Acyclic 4-edge colouring of non-regular subcubic graphs in linear time

An acyclic k-edge-colouring is an assignment of colours from {1,2,…,k} to the edges of a simple graph G such that adjacent edges have different colours and each circuit of G contains edges of at least three colours. We describe a linear time algorithm to construct an acyclic 4-edge-colouring of a connected subcubic graph that is not cubic.

Linear Recognition and Embedding of Fibonacci Cubes

Fibonacci strings are binary strings that contain no two consecutive 1s. The Fibonacci cube Γ h is the subgraph of the h-cube induced by the Fibonacci strings. These graphs are applicable as interconnection networks and in theoretical chemistry, and lead to the Fibonacci dimension of a graph. We derive a new characterization of Fibonacci cubes. The characterization is the basis for an algorithm which recognizes these graphs in linear time. Moreover, a graph which was recognized as a Fibonacci cube can be embedded into a hypercube using Fibonacci strings within the same time bound.