17,552 research outputs found
Lower Bounds for Symbolic Computation on Graphs: Strongly Connected Components, Liveness, Safety, and Diameter
A model of computation that is widely used in the formal analysis of reactive
systems is symbolic algorithms. In this model the access to the input graph is
restricted to consist of symbolic operations, which are expensive in comparison
to the standard RAM operations. We give lower bounds on the number of symbolic
operations for basic graph problems such as the computation of the strongly
connected components and of the approximate diameter as well as for fundamental
problems in model checking such as safety, liveness, and co-liveness. Our lower
bounds are linear in the number of vertices of the graph, even for
constant-diameter graphs. For none of these problems lower bounds on the number
of symbolic operations were known before. The lower bounds show an interesting
separation of these problems from the reachability problem, which can be solved
with symbolic operations, where is the diameter of the graph.
Additionally we present an approximation algorithm for the graph diameter
which requires symbolic steps to achieve a
-approximation for any constant . This compares to
symbolic steps for the (naive) exact algorithm and
symbolic steps for a 2-approximation. Finally we also give a refined analysis
of the strongly connected components algorithms of Gentilini et al., showing
that it uses an optimal number of symbolic steps that is proportional to the
sum of the diameters of the strongly connected components
On tree-decompositions of one-ended graphs
A graph is one-ended if it contains a ray (a one way infinite path) and
whenever we remove a finite number of vertices from the graph then what remains
has only one component which contains rays. A vertex {\em dominates} a ray
in the end if there are infinitely many paths connecting to the ray such
that any two of these paths have only the vertex in common. We prove that
if a one-ended graph contains no ray which is dominated by a vertex and no
infinite family of pairwise disjoint rays, then it has a tree-decomposition
such that the decomposition tree is one-ended and the tree-decomposition is
invariant under the group of automorphisms.
This can be applied to prove a conjecture of Halin from 2000 that the
automorphism group of such a graph cannot be countably infinite and solves a
recent problem of Boutin and Imrich. Furthermore, it implies that every
transitive one-ended graph contains an infinite family of pairwise disjoint
rays
Bidimensionality and EPTAS
Bidimensionality theory is a powerful framework for the development of
metaalgorithmic techniques. It was introduced by Demaine et al. as a tool to
obtain sub-exponential time parameterized algorithms for problems on H-minor
free graphs. Demaine and Hajiaghayi extended the theory to obtain PTASs for
bidimensional problems, and subsequently improved these results to EPTASs.
Fomin et. al related the theory to the existence of linear kernels for
parameterized problems. In this paper we revisit bidimensionality theory from
the perspective of approximation algorithms and redesign the framework for
obtaining EPTASs to be more powerful, easier to apply and easier to understand.
Two of the most widely used approaches to obtain PTASs on planar graphs are
the Lipton-Tarjan separator based approach, and Baker's approach. Demaine and
Hajiaghayi strengthened both approaches using bidimensionality and obtained
EPTASs for a multitude of problems. We unify the two strenghtened approaches to
combine the best of both worlds. At the heart of our framework is a
decomposition lemma which states that for "most" bidimensional problems, there
is a polynomial time algorithm which given an H-minor-free graph G as input and
an e > 0 outputs a vertex set X of size e * OPT such that the treewidth of G n
X is f(e). Here, OPT is the objective function value of the problem in question
and f is a function depending only on e. This allows us to obtain EPTASs on
(apex)-minor-free graphs for all problems covered by the previous framework, as
well as for a wide range of packing problems, partial covering problems and
problems that are neither closed under taking minors, nor contractions. To the
best of our knowledge for many of these problems including cycle packing,
vertex-h-packing, maximum leaf spanning tree, and partial r-dominating set no
EPTASs on planar graphs were previously known
On the size of identifying codes in triangle-free graphs
In an undirected graph , a subset such that is a
dominating set of , and each vertex in is dominated by a distinct
subset of vertices from , is called an identifying code of . The concept
of identifying codes was introduced by Karpovsky, Chakrabarty and Levitin in
1998. For a given identifiable graph , let \M(G) be the minimum
cardinality of an identifying code in . In this paper, we show that for any
connected identifiable triangle-free graph on vertices having maximum
degree , \M(G)\le n-\tfrac{n}{\Delta+o(\Delta)}. This bound is
asymptotically tight up to constants due to various classes of graphs including
-ary trees, which are known to have their minimum identifying code
of size . We also provide improved bounds for
restricted subfamilies of triangle-free graphs, and conjecture that there
exists some constant such that the bound \M(G)\le n-\tfrac{n}{\Delta}+c
holds for any nontrivial connected identifiable graph
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