Pathwidth of cubic graphs and exact algorithms

We prove that for any ?>0 there exists an integer n? such that the pathwidth of every cubic (or 3-regular) graph on n>n? vertices is at most (1/6+?)n. Based on this bound we improve the worst case time analysis for a number of exact exponential algorithms on graphs of maximum vertex degree three.     

A refined search tree technique for Dominating Set on planar graphs

We establish a refined search tree technique for the parameterized DOMINATING SET problem on planar graphs. Here, we are given an undirected graph and we ask for a set of at most k vertices such that every other vertex has at least one neighbor in this set. We describe algorithms with running times O(8^kn) and O(8^kk+n³), where n is the number of vertices in the graph, based on bounded search trees. We describe a set of polynomial time data-reduction rules for a more general “annotated” problem on black/white graphs that asks for a set of k vertices (black or white) that dominate all the black vertices. An intricate argument based on the Euler formula then establishes an efficient branching strategy for reduced inputs to this problem. In addition, we give a family examples showing that the bound of the branching theorem is optimal with respect to our reduction rules. Our final search tree algorithm is easy to implement; its analysis, however, is involved.     

Comparing the strength of query types in property testing: The case of k-colorability

We study the power of four query models in the context of property testing in general graphs, where our main case study is the problem of testing k-colorability. Two query types, which have been studied extensively in the past, are pair queries and neighbor queries. The former corresponds to asking whether there is an edge between any particular pair of vertices, and the latter to asking for the i ^th neighbor of a particular vertex. We show that while for pair queries testing k-colorability requires a number of queries that is a monotone decreasing function in the average degree d, the query complexity in the case of neighbor queries remains roughly the same for every density and for large values of k. We also consider a combined model that allows both types of queries, and we propose a new, stronger, query model, related to the field of Group Testing. We give upper and lower bounds on the query complexity for one-sided error in all the models, where the bounds are nearly tight for three of the models. In some of the cases, our lower bounds extend to two-sided error algorithms. The problem of testing k-colorability was previously studied in the contexts of dense graphs and of sparse graphs, and in our proofs we unify approaches from those cases, and also provide some new tools and techniques that may be of independent interest.     

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.     

Broadcast in the rendezvous model

In many large, distributed or mobile networks, broadcast algorithms are used to update information stored at the nodes. In this paper, we propose a new model of communication based on rendezvous and analyze a multi-hop distributed algorithm to broadcast a message in a synchronous setting. In the rendezvous model, two neighbors u and v can communicate if and only if u calls v and v calls u simultaneously. Thus nodes u and v obtain a rendezvous at a meeting point. If m is the number of meeting points, the network can be modeled by a graph of n vertices and m edges. At each round, every vertex chooses a random neighbor and there is a rendezvous if an edge has been chosen by its two extremities. Rendezvous enable an exchange of information between the two entities. We get sharp lower and upper bounds on the time complexity in terms of number of rounds to broadcast: we show that, for any graph, the expected number of rounds is between ln n and O (n²). For these two bounds, we prove that there exist some graphs for which the expected number of rounds is either O (ln (n)) or Ω (n²). For specific topologies, additional bounds are given.     

On Reversible Cascades in Scale-Free and Erdős-Rényi Random Graphs

Consider the following cascading process on a simple undirected graph G(V,E) with diameter Δ. In round zero, a set S?V of vertices, called the seeds, are active. In round i+1, i∈?, a non-isolated vertex is activated if at least a ρ∈(0,1] fraction of its neighbors are active in round i; it is deactivated otherwise. For k∈?, let min-seed^(k)(G,ρ) be the minimum number of seeds needed to activate all vertices in or before round k. This paper derives upper bounds on min-seed^(k)(G,ρ). In particular, if G is connected and there exist constants C>0 and γ>2 such that the fraction of degree-k vertices in G is at most C/k ^γ for all k∈?⁺, then min-seed^(Δ)(G,ρ)=O(?ρ ^γ?1|V|?). Furthermore, for n∈?⁺, p=Ω((ln(e/ρ))/(ρn)) and with probability 1?exp(?n ^Ω(1)) over the Erd?s-Rényi random graphs G(n,p), min-seed⁽¹⁾(G(n,p),ρ)=O(ρn).     

Hamiltonicity in connected regular graphs

In 1980, Jackson proved that every 2-connected k-regular graph with at most 3k vertices is Hamiltonian. This result has been extended in several papers. In this note, we determine the minimum number of vertices in a connected k-regular graph that is not Hamiltonian, and we also solve the analogous problem for Hamiltonian paths. Further, we characterize the smallest connected k-regular graphs without a Hamiltonian cycle.     

Parameterized algorithm for eternal vertex cover

In this paper we initiate the study of a “dynamic” variant of the classical Vertex Cover problem, the Eternal Vertex Cover problem introduced by Klostermeyer and Mynhardt, from the perspective of parameterized algorithms. This problem consists in placing a minimum number of guards on the vertices of a graph such that these guards can protect the graph from any sequence of attacks on its edges. In response to an attack, each guard is allowed either to stay in his vertex, or to move to a neighboring vertex. However, at least one guard has to fix the attacked edge by moving along it. The other guards may move to reconfigure and prepare for the next attack. Thus at every step the vertices occupied by guards form a vertex cover. We show that the problem admits a kernel of size k⁴(k+1)+2k, which shows that the problem is fixed parameter tractable when parameterized by the number of available guards k. Finally, we also provide an algorithm with running time O(²O(k²)+nm) for Eternal Vertex Cover, where n is the number of vertices and m the number of edges of the input graph. In passing we also observe that Eternal Vertex Cover is NP-hard, yet it has a polynomial time 2-approximation algorithm.     

Randomized parallel list ranking for distributed memory multiprocessors

We present a randomized parallel list ranking algorithm for distributed memory multiprocessors, using a BSP type model. We first describe a simple version which requires, with high probability, log(3p)+log ln(n)=Õ(logp+log logn) communication rounds (h-relations withh=Õ(n/p)) andÕ(n/p)) local computation. We then outline an improved version that requires high probability, onlyr?(4k+6) log(2/3p)+8=Õ(k logp) communication rounds wherek=min{i?0 |ln(i+1)n?(2/3p)²ⁱ⁺¹}. Notekn) is an extremely small number. Forn andp?4, the value ofk is at most 2. Hence, for a given number of processors,p, the number of communication rounds required is, for all practical purposes, independent ofn. Forn?1, 500,000 and 4?p?2048, the number of communication rounds in our algorithm is bounded, with high probability, by 78, but the actual number of communication rounds observed so far is 25 in the worst case. Forn?10010100 and 4?p?2048, the number of communication rounds in our algorithm is bounded, with high probability, by 118; and we conjecture that the actual number of communication rounds required will not exceed 50. Our algorithm has a considerably smaller member of communication rounds than the list ranking algorithm used in Reid-Miller’s empirical study of parallel list ranking on the Cray C-90.⁽¹⁾ To our knowledge, Reid-Miller’s algorithm⁽¹⁾ was the fastest list ranking implementation so far. Therefore, we expect that our result will have considerable practical relevance.     

Many Distances in Planar Graphs

We show how to compute in O(n ^4/3log?^1/3 n+n ^2/3 k ^2/3log?n) time the distance between k given pairs of vertices of a planar graph G with n vertices. This improves previous results whenever (n/log?n)^5/6≤k≤n ²/log?⁶ n. As an application, we speed up previous algorithms for computing the dilation of geometric planar graphs.     

Faster Algorithms for All-Pairs Small Stretch Distances in Weighted Graphs

Let G=(V,E) be a weighted undirected graph, with non-negative edge weights. We consider the problem of efficiently computing approximate distances between all pairs of vertices in?G. While many efficient algorithms are known for this problem in unweighted graphs, not many results are known for this problem in weighted graphs. Zwick?(J. Assoc. Comput. Mach. 49:289–317, 2002) showed that for any fixed ε>0, stretch 1+ε distances (a path in G between u,v∈V is said to be of stretch t if its length is at most t times the distance between u and v in G) between all pairs of vertices in a weighted directed graph on n vertices can be computed in $\tilde{O}(n^{\omega})$ time, where ω<2.376 is the exponent of matrix multiplication and n is the number of vertices. It is known that finding distances of stretch less than 2 between all pairs of vertices in G is at least as hard as Boolean matrix multiplication of two n×n matrices. Here we show that all pairs stretch 2+ε distances for any fixed ε>0 in G can be computed in expected time O(n ^9/4). This algorithm uses a fast rectangular matrix multiplication subroutine. We also present a combinatorial algorithm (that is, it does not use fast matrix multiplication) with expected running time O(n ^9/4) for computing all-pairs stretch 5/2 distances in?G. This combinatorial algorithm will serve as a key step in our all-pairs stretch 2+ε distances algorithm.     

Schnyder Decompositions for Regular Plane Graphs and Application to Drawing

Schnyder woods are decompositions of simple triangulations into three edge-disjoint spanning trees crossing each other in a specific way. In this article, we generalize the definition of Schnyder woods to d-angulations (plane graphs with faces of degree d) for all d≥3. A Schnyder decomposition is a set of d spanning forests crossing each other in a specific way, and such that each internal edge is part of exactly d?2 of the spanning forests. We show that a Schnyder decomposition exists if and only if the girth of the d-angulation is d. As in the case of Schnyder woods (d=3), there are alternative formulations in terms of orientations (“fractional” orientations when d≥5) and in terms of corner-labellings. Moreover, the set of Schnyder decompositions of a fixed d-angulation of girth d has a natural structure of distributive lattice. We also study the dual of Schnyder decompositions which are defined on d-regular plane graphs of mincut d with a distinguished vertex v ^?: these are sets of d spanning trees rooted at v ^? crossing each other in a specific way and such that each edge not incident to v ^? is used by two trees in opposite directions. Additionally, for even values of d, we show that a subclass of Schnyder decompositions, which are called even, enjoy additional properties that yield a reduced formulation; in the case d=4, these correspond to well-studied structures on simple quadrangulations (2-orientations and partitions into 2 spanning trees). In the case d=4, we obtain straight-line and orthogonal planar drawing algorithms by using the dual of even Schnyder decompositions. For a 4-regular plane graph G of mincut 4 with a distinguished vertex v ^? and n?1 other vertices, our algorithms places the vertices of G\v ^? on a (n?2)×(n?2) grid according to a permutation pattern, and in the orthogonal drawing each of the 2n?4 edges of G\v ^? has exactly one bend. The vertex v ^? can be embedded at the cost of 3 additional rows and columns, and 8 additional bends. We also describe a further compaction step for the drawing algorithms and show that the obtained grid-size is strongly concentrated around 25n/32×25n/32 for a uniformly random instance with n vertices.     

Optimal parallel algorithms for multiple updates of minimum spanning trees

Parallel updates of minimum spanning trees (MSTs) have been studied in the past. These updates allowed a single change in the underlying graph, such as a change in the cost of an edge or an insertion of a new vertex. Multiple update problems for MSTs are concerned with handling more than one such change. In the sequential case multiple update problems may be solved using repeated applications of an efficient algorithm for a single update. However, for efficiency reasons, parallel algorithms for multiple update problems must consider all changes to the underlying graph simultaneously. In this paper we describe parallel algorithms for updating an MST whenk new vertices are inserted or deleted in the underlying graph, when the costs ofk edges are changed, or whenk edge insertions and deletions are performed. For multiple vertex insertion update, our algorithm achieves time and processor bounds ofO(log n·logk) and nk/(logn·logk), respectively, on a CREW parallel random access machine. These bounds are optimal for dense graphs. A novel feature of this algorithm is a transformation of the previous MST andk new vertices to a bipartite graph which enables us to obtain the above-mentioned bounds.     

Efficient parallel algorithms for path problems in directed graphs

In this paper we describe a technique for finding efficient parallel algorithms for problems on directed graphs that involve checking the existence of certain kinds of paths in the graph. This technique provides efficient algorithms for finding dominators in flow graphs, performing interval and loop analysis on reducible flow graphs, and finding the feedback vertices of a digraph. Each of these algorithms takesO(log² n) time using the same number of processors needed for fast matrix multiplication. All of these bounds are for an EREW PRAM.     

Algorithms for maximum weight induced paths

A family of graphs is a k-bounded-hole family if every graph in the family has no holes with more than k vertices. The problem of finding in a graph a maximum weight induced path has applications in large communication and neural networks when worst case communication time needs to be evaluated; unfortunately this problem is NP-hard even when restricted to bipartite graphs. We show that this problem has polynomial time algorithms for k-bounded-hole families of graphs, for interval-filament graphs and for graphs decomposable by clique cut-sets or by splits into prime subgraphs for which such algorithms exist.     

On Cutwidth Parameterized by Vertex Cover

We study the Cutwidth problem, where the input is a graph G, and the objective is find a linear layout of the vertices that minimizes the maximum number of edges intersected by any vertical line inserted between two consecutive vertices. We give an algorithm for Cutwidth with running time O(2 ^k n ^O(1)). Here k is the size of a minimum vertex cover of the input graph G, and n is the number of vertices in G. Our algorithm gives an O(2 ^n/2 n ^O(1)) time algorithm for Cutwidth on bipartite graphs as a corollary. This is the first non-trivial exact exponential time algorithm for Cutwidth on a graph class where the problem remains NP-complete. Additionally, we show that Cutwidth parameterized by the size of the minimum vertex cover of the input graph does not admit a polynomial kernel unless NP?coNP/poly. Our kernelization lower bound contrasts with the recent results of Bodlaender et al. (ICALP, Springer, Berlin, 2011; SWAT, Springer, Berlin, 2012) that both Treewidth and Pathwidth parameterized by vertex cover do admit polynomial kernels.     

Path embeddings in faulty 3-ary n-cubes

The class of k-ary n-cubes represents the most commonly used interconnection topology for distributed-memory parallel systems. In this paper, we study the problem of embedding paths of various lengths into faulty 3-ary n-cubes and prove that a faulty 3-ary n-cube with f?2n-3 faulty vertices admits a path of every length from 2n-1 to 3ⁿ-f-1 connecting any two distinct healthy vertices. This result is optimal with respect to the number of vertex faults tolerated.     

Improved algorithms for recognizing p-Helly and hereditary p-Helly hypergraphs

A hypergraph H is set of vertices V together with a collection of nonempty subsets of it, called the hyperedges of H. A partial hypergraph of H is a hypergraph whose hyperedges are all hyperedges of H, whereas for V^′⊆V the subhypergraph (induced by V^′) is a hypergraph with vertices V^′ and having as hyperedges the subsets obtained as nonempty intersections of V^′ and each of the hyperedges of H. For p?1 say that H is p-intersecting when every subset formed by p hyperedges of H contain a common vertex. Say that H is p-Helly when every p-intersecting partial hypergraph H^′ of H contains a vertex belonging to all the hyperedges of H^′. A hypergraph is hereditary p-Helly when every (induced) subhypergraph of it is p-Helly. In this paper we describe new characterizations for hereditary p-Helly hypergraphs and discuss the recognition problems for both p-Helly and hereditary p-Helly hypergraphs. The proposed algorithms improve the complexity of the existing recognition algorithms.     

Subexponential algorithms for partial cover problems

Partial Cover problems are optimization versions of fundamental and well-studied problems like Vertex Cover and Dominating Set. Here one is interested in covering (or dominating) the maximum number of edges (or vertices) using a given number k of vertices, rather than covering all edges (or vertices). In general graphs, these problems are hard for parameterized complexity classes when parameterized by k. It was recently shown by Amini et al. (2008) [1] that Partial Vertex Cover and Partial Dominating Set are fixed parameter tractable on large classes of sparse graphs, namely H-minor-free graphs, which include planar graphs and graphs of bounded genus. In particular, it was shown that on planar graphs both problems can be solved in time ²O(k)nO(1).During the last decade there has been an extensive study on parameterized subexponential algorithms. In particular, it was shown that the classical Vertex Cover and Dominating Set problems can be solved in subexponential time on H-minor-free graphs. The techniques developed to obtain subexponential algorithms for classical problems do not apply to partial cover problems. It was left as an open problem by Amini et al. (2008) [1] whether there is a subexponential algorithm for Partial Vertex Cover and Partial Dominating Set. In this paper, we answer the question affirmatively by solving both problems in time not only on planar graphs but also on much larger classes of graphs, namely, apex-minor-free graphs. Compared to previously known algorithms for these problems our algorithms are significantly faster and simpler.