16 research outputs found

    Universal graphs and universal permutations

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    Let XX be a family of graphs and XnX_n the set of nn-vertex graphs in XX. A graph U(n)U^{(n)} containing all graphs from XnX_n as induced subgraphs is called nn-universal for XX. Moreover, we say that U(n)U^{(n)} is a proper nn-universal graph for XX if it belongs to XX. In the present paper, we construct a proper nn-universal graph for the class of split permutation graphs. Our solution includes two ingredients: a proper universal 321-avoiding permutation and a bijection between 321-avoiding permutations and symmetric split permutation graphs. The nn-universal split permutation graph constructed in this paper has 4n34n^3 vertices, which means that this construction is order-optimal.Comment: To appear in Discrete Mathematics, Algorithms and Application

    Dynamic and Multi-functional Labeling Schemes

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    We investigate labeling schemes supporting adjacency, ancestry, sibling, and connectivity queries in forests. In the course of more than 20 years, the existence of logn+O(loglog)\log n + O(\log \log) labeling schemes supporting each of these functions was proven, with the most recent being ancestry [Fraigniaud and Korman, STOC '10]. Several multi-functional labeling schemes also enjoy lower or upper bounds of logn+Ω(loglogn)\log n + \Omega(\log \log n) or logn+O(loglogn)\log n + O(\log \log n) respectively. Notably an upper bound of logn+5loglogn\log n + 5\log \log n for adjacency+siblings and a lower bound of logn+loglogn\log n + \log \log n for each of the functions siblings, ancestry, and connectivity [Alstrup et al., SODA '03]. We improve the constants hidden in the OO-notation. In particular we show a logn+2loglogn\log n + 2\log \log n lower bound for connectivity+ancestry and connectivity+siblings, as well as an upper bound of logn+3loglogn+O(logloglogn)\log n + 3\log \log n + O(\log \log \log n) for connectivity+adjacency+siblings by altering existing methods. In the context of dynamic labeling schemes it is known that ancestry requires Ω(n)\Omega(n) bits [Cohen, et al. PODS '02]. In contrast, we show upper and lower bounds on the label size for adjacency, siblings, and connectivity of 2logn2\log n bits, and 3logn3 \log n to support all three functions. There exist efficient adjacency labeling schemes for planar, bounded treewidth, bounded arboricity and interval graphs. In a dynamic setting, we show a lower bound of Ω(n)\Omega(n) for each of those families.Comment: 17 pages, 5 figure

    Distance labeling schemes for trees

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    We consider distance labeling schemes for trees: given a tree with nn nodes, label the nodes with binary strings such that, given the labels of any two nodes, one can determine, by looking only at the labels, the distance in the tree between the two nodes. A lower bound by Gavoille et. al. (J. Alg. 2004) and an upper bound by Peleg (J. Graph Theory 2000) establish that labels must use Θ(log2n)\Theta(\log^2 n) bits\footnote{Throughout this paper we use log\log for log2\log_2.}. Gavoille et. al. (ESA 2001) show that for very small approximate stretch, labels use Θ(lognloglogn)\Theta(\log n \log \log n) bits. Several other papers investigate various variants such as, for example, small distances in trees (Alstrup et. al., SODA'03). We improve the known upper and lower bounds of exact distance labeling by showing that 14log2n\frac{1}{4} \log^2 n bits are needed and that 12log2n\frac{1}{2} \log^2 n bits are sufficient. We also give (1+ϵ1+\epsilon)-stretch labeling schemes using Θ(logn)\Theta(\log n) bits for constant ϵ>0\epsilon>0. (1+ϵ1+\epsilon)-stretch labeling schemes with polylogarithmic label size have previously been established for doubling dimension graphs by Talwar (STOC 2004). In addition, we present matching upper and lower bounds for distance labeling for caterpillars, showing that labels must have size 2lognΘ(loglogn)2\log n - \Theta(\log\log n). For simple paths with kk nodes and edge weights in [1,n][1,n], we show that labels must have size k1klogn+Θ(logk)\frac{k-1}{k}\log n+\Theta(\log k)

    Labeling Schemes for Bounded Degree Graphs

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    We investigate adjacency labeling schemes for graphs of bounded degree Δ=O(1)\Delta = O(1). In particular, we present an optimal (up to an additive constant) logn+O(1)\log n + O(1) adjacency labeling scheme for bounded degree trees. The latter scheme is derived from a labeling scheme for bounded degree outerplanar graphs. Our results complement a similar bound recently obtained for bounded depth trees [Fraigniaud and Korman, SODA 10], and may provide new insights for closing the long standing gap for adjacency in trees [Alstrup and Rauhe, FOCS 02]. We also provide improved labeling schemes for bounded degree planar graphs. Finally, we use combinatorial number systems and present an improved adjacency labeling schemes for graphs of bounded degree Δ\Delta with (e+1)n<Δn/5(e+1)\sqrt{n} < \Delta \leq n/5

    Simpler, faster and shorter labels for distances in graphs

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    We consider how to assign labels to any undirected graph with n nodes such that, given the labels of two nodes and no other information regarding the graph, it is possible to determine the distance between the two nodes. The challenge in such a distance labeling scheme is primarily to minimize the maximum label lenght and secondarily to minimize the time needed to answer distance queries (decoding). Previous schemes have offered different trade-offs between label lengths and query time. This paper presents a simple algorithm with shorter labels and shorter query time than any previous solution, thereby improving the state-of-the-art with respect to both label length and query time in one single algorithm. Our solution addresses several open problems concerning label length and decoding time and is the first improvement of label length for more than three decades. More specifically, we present a distance labeling scheme with label size (log 3)/2 + o(n) (logarithms are in base 2) and O(1) decoding time. This outperforms all existing results with respect to both size and decoding time, including Winkler's (Combinatorica 1983) decade-old result, which uses labels of size (log 3)n and O(n/log n) decoding time, and Gavoille et al. (SODA'01), which uses labels of size 11n + o(n) and O(loglog n) decoding time. In addition, our algorithm is simpler than the previous ones. In the case of integral edge weights of size at most W, we present almost matching upper and lower bounds for label sizes. For r-additive approximation schemes, where distances can be off by an additive constant r, we give both upper and lower bounds. In particular, we present an upper bound for 1-additive approximation schemes which, in the unweighted case, has the same size (ignoring second order terms) as an adjacency scheme: n/2. We also give results for bipartite graphs and for exact and 1-additive distance oracles

    Adjacency labeling schemes and induced-universal graphs

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    We describe a way of assigning labels to the vertices of any undirected graph on up to nn vertices, each composed of n/2+O(1)n/2+O(1) bits, such that given the labels of two vertices, and no other information regarding the graph, it is possible to decide whether or not the vertices are adjacent in the graph. This is optimal, up to an additive constant, and constitutes the first improvement in almost 50 years of an n/2+O(logn)n/2+O(\log n) bound of Moon. As a consequence, we obtain an induced-universal graph for nn-vertex graphs containing only O(2n/2)O(2^{n/2}) vertices, which is optimal up to a multiplicative constant, solving an open problem of Vizing from 1968. We obtain similar tight results for directed graphs, tournaments and bipartite graphs

    Near-Optimal Induced Universal Graphs for Bounded Degree Graphs

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    A graph UU is an induced universal graph for a family FF of graphs if every graph in FF is a vertex-induced subgraph of UU. For the family of all undirected graphs on nn vertices Alstrup, Kaplan, Thorup, and Zwick [STOC 2015] give an induced universal graph with O ⁣(2n/2)O\!\left(2^{n/2}\right) vertices, matching a lower bound by Moon [Proc. Glasgow Math. Assoc. 1965]. Let k=D/2k= \lceil D/2 \rceil. Improving asymptotically on previous results by Butler [Graphs and Combinatorics 2009] and Esperet, Arnaud and Ochem [IPL 2008], we give an induced universal graph with O ⁣(k2kk!nk)O\!\left(\frac{k2^k}{k!}n^k \right) vertices for the family of graphs with nn vertices of maximum degree DD. For constant DD, Butler gives a lower bound of Ω ⁣(nD/2)\Omega\!\left(n^{D/2}\right). For an odd constant D3D\geq 3, Esperet et al. and Alon and Capalbo [SODA 2008] give a graph with O ⁣(nk1D)O\!\left(n^{k-\frac{1}{D}}\right) vertices. Using their techniques for any (including constant) even values of DD gives asymptotically worse bounds than we present. For large DD, i.e. when D=Ω(log3n)D = \Omega\left(\log^3 n\right), the previous best upper bound was (nD/2)nO(1){n\choose\lceil D/2\rceil} n^{O(1)} due to Adjiashvili and Rotbart [ICALP 2014]. We give upper and lower bounds showing that the size is (n/2D/2)2±O~(D){\lfloor n/2\rfloor\choose\lfloor D/2 \rfloor}2^{\pm\tilde{O}\left(\sqrt{D}\right)}. Hence the optimal size is 2O~(D)2^{\tilde{O}(D)} and our construction is within a factor of 2O~(D)2^{\tilde{O}\left(\sqrt{D}\right)} from this. The previous results were larger by at least a factor of 2Ω(D)2^{\Omega(D)}. As a part of the above, proving a conjecture by Esperet et al., we construct an induced universal graph with 2n12n-1 vertices for the family of graphs with max degree 22. In addition, we give results for acyclic graphs with max degree 22 and cycle graphs. Our results imply the first labeling schemes that for any DD are at most o(n)o(n) bits from optimal

    Quasipolynomiality of the Smallest Missing Induced Subgraph

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    We study the problem of finding the smallest graph that does not occur as an induced subgraph of a given graph. This missing induced subgraph has at most logarithmic size and can be found by a brute-force search, in an nn-vertex graph, in time nO(logn)n^{O(\log n)}. We show that under the Exponential Time Hypothesis this quasipolynomial time bound is optimal. We also consider variations of the problem in which either the missing subgraph or the given graph comes from a restricted graph family; for instance, we prove that the smallest missing planar induced subgraph of a given planar graph can be found in polynomial time.Comment: 10 pages, 1 figure. To appear in J. Graph Algorithms Appl. This version updates an author affiliatio
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