533 research outputs found
Deciding first-order properties of nowhere dense graphs
Nowhere dense graph classes, introduced by Nesetril and Ossona de Mendez,
form a large variety of classes of "sparse graphs" including the class of
planar graphs, actually all classes with excluded minors, and also bounded
degree graphs and graph classes of bounded expansion.
We show that deciding properties of graphs definable in first-order logic is
fixed-parameter tractable on nowhere dense graph classes. At least for graph
classes closed under taking subgraphs, this result is optimal: it was known
before that for all classes C of graphs closed under taking subgraphs, if
deciding first-order properties of graphs in C is fixed-parameter tractable,
then C must be nowhere dense (under a reasonable complexity theoretic
assumption).
As a by-product, we give an algorithmic construction of sparse neighbourhood
covers for nowhere dense graphs. This extends and improves previous
constructions of neighbourhood covers for graph classes with excluded minors.
At the same time, our construction is considerably simpler than those. Our
proofs are based on a new game-theoretic characterisation of nowhere dense
graphs that allows for a recursive version of locality-based algorithms on
these classes. On the logical side, we prove a "rank-preserving" version of
Gaifman's locality theorem.Comment: 30 page
Random local algorithms
Consider the problem when we want to construct some structure on a bounded
degree graph, e.g. an almost maximum matching, and we want to decide about each
edge depending only on its constant radius neighbourhood. We show that the
information about the local statistics of the graph does not help here. Namely,
if there exists a random local algorithm which can use any local statistics
about the graph, and produces an almost optimal structure, then the same can be
achieved by a random local algorithm using no statistics.Comment: 9 page
Slime mould imitation of Belgian transport networks: redundancy, bio-essential motorways, and dissolution
Belgium is amongst few artificial countries, established on purpose, when
Dutch and French speaking parts were joined in a single unit. This makes
Belgium a particularly interesting testbed for studying bio-inspired techniques
for simulation and analysis of vehicular transport networks. We imitate growth
and formation of a transport network between major urban areas in Belgium using
the acellular slime mould Physarum polycephalum. We represent the urban areas
with the sources of nutrients. The slime mould spans the sources of nutrients
with a network of protoplasmic tubes. The protoplasmic tubes represent the
motorways. In an experimental laboratory analysis we compare the motorway
network approximated by P. polycephalum and the man-made motorway network of
Belgium. We evaluate the efficiency of the slime mould network and the motorway
network using proximity graphs
Streaming Complexity of Spanning Tree Computation
The semi-streaming model is a variant of the streaming model frequently used for the computation of graph problems. It allows the edges of an n-node input graph to be read sequentially in p passes using OÌ(n) space. If the list of edges includes deletions, then the model is called the turnstile model; otherwise it is called the insertion-only model. In both models, some graph problems, such as spanning trees, k-connectivity, densest subgraph, degeneracy, cut-sparsifier, and (Î+1)-coloring, can be exactly solved or (1+Δ)-approximated in a single pass; while other graph problems, such as triangle detection and unweighted all-pairs shortest paths, are known to require ΩÌ(n) passes to compute. For many fundamental graph problems, the tractability in these models is open. In this paper, we study the tractability of computing some standard spanning trees, including BFS, DFS, and maximum-leaf spanning trees. Our results, in both the insertion-only and the turnstile models, are as follows.
Maximum-Leaf Spanning Trees: This problem is known to be APX-complete with inapproximability constant Ï â [245/244, 2). By constructing an Δ-MLST sparsifier, we show that for every constant Δ > 0, MLST can be approximated in a single pass to within a factor of 1+Δ w.h.p. (albeit in super-polynomial time for Δ †Ï-1 assuming P â NP) and can be approximated in polynomial time in a single pass to within a factor of Ï_n+Δ w.h.p., where Ï_n is the supremum constant that MLST cannot be approximated to within using polynomial time and OÌ(n) space. In the insertion-only model, these algorithms can be deterministic.
BFS Trees: It is known that BFS trees require Ï(1) passes to compute, but the naĂŻve approach needs O(n) passes. We devise a new randomized algorithm that reduces the pass complexity to O(ân), and it offers a smooth tradeoff between pass complexity and space usage. This gives a polynomial separation between single-source and all-pairs shortest paths for unweighted graphs.
DFS Trees: It is unknown whether DFS trees require more than one pass. The current best algorithm by Khan and Mehta [STACS 2019] takes OÌ(h) passes, where h is the height of computed DFS trees. Note that h can be as large as Ω(m/n) for n-node m-edge graphs. Our contribution is twofold. First, we provide a simple alternative proof of this result, via a new connection to sparse certificates for k-node-connectivity. Second, we present a randomized algorithm that reduces the pass complexity to O(ân), and it also offers a smooth tradeoff between pass complexity and space usage.ISSN:1868-896
Minimizing movement: Fixed-parameter tractability
We study an extensive class of movement minimization problems that arise from many practical scenarios but so far have little theoretical study. In general, these problems involve planning the coordinated motion of a collection of agents (representing robots, people, map labels, network messages, etc.) to achieve a global property in the network while minimizing the maximum or average movement (expended energy). The only previous theoretical results about this class of problems are about approximation and are mainly negative: many movement problems of interest have polynomial inapproximability. Given that the number of mobile agents is typically much smaller than the complexity of the environment, we turn to fixed-parameter tractability. We characterize the boundary between tractable and intractable movement problems in a very general setup: it turns out the complexity of the problem fundamentally depends on the treewidth of the minimal configurations. Thus, the complexity of a particular problem can be determined by answering a purely combinatorial question. Using our general tools, we determine the complexity of several concrete problems and fortunately show that many movement problems of interest can be solved efficiently.</jats:p
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