9,095 research outputs found

    Improved Compact Visibility Representation of Planar Graph via Schnyder's Realizer

    Full text link
    Let GG be an nn-node planar graph. In a visibility representation of GG, each node of GG is represented by a horizontal line segment such that the line segments representing any two adjacent nodes of GG are vertically visible to each other. In the present paper we give the best known compact visibility representation of GG. Given a canonical ordering of the triangulated GG, our algorithm draws the graph incrementally in a greedy manner. We show that one of three canonical orderings obtained from Schnyder's realizer for the triangulated GG yields a visibility representation of GG no wider than 22n4015\frac{22n-40}{15}. Our easy-to-implement O(n)-time algorithm bypasses the complicated subroutines for four-connected components and four-block trees required by the best previously known algorithm of Kant. Our result provides a negative answer to Kant's open question about whether 3n62\frac{3n-6}{2} is a worst-case lower bound on the required width. Also, if GG has no degree-three (respectively, degree-five) internal node, then our visibility representation for GG is no wider than 4n93\frac{4n-9}{3} (respectively, 4n73\frac{4n-7}{3}). Moreover, if GG is four-connected, then our visibility representation for GG is no wider than n1n-1, matching the best known result of Kant and He. As a by-product, we obtain a much simpler proof for a corollary of Wagner's Theorem on realizers, due to Bonichon, Sa\"{e}c, and Mosbah.Comment: 11 pages, 6 figures, the preliminary version of this paper is to appear in Proceedings of the 20th Annual Symposium on Theoretical Aspects of Computer Science (STACS), Berlin, Germany, 200

    Orderly Spanning Trees with Applications

    Full text link
    We introduce and study the {\em orderly spanning trees} of plane graphs. This algorithmic tool generalizes {\em canonical orderings}, which exist only for triconnected plane graphs. Although not every plane graph admits an orderly spanning tree, we provide an algorithm to compute an {\em orderly pair} for any connected planar graph GG, consisting of a plane graph HH of GG, and an orderly spanning tree of HH. We also present several applications of orderly spanning trees: (1) a new constructive proof for Schnyder's Realizer Theorem, (2) the first area-optimal 2-visibility drawing of GG, and (3) the best known encodings of GG with O(1)-time query support. All algorithms in this paper run in linear time.Comment: 25 pages, 7 figures, A preliminary version appeared in Proceedings of the 12th Annual ACM-SIAM Symposium on Discrete Algorithms (SODA 2001), Washington D.C., USA, January 7-9, 2001, pp. 506-51

    Compact Floor-Planning via Orderly Spanning Trees

    Full text link
    Floor-planning is a fundamental step in VLSI chip design. Based upon the concept of orderly spanning trees, we present a simple O(n)-time algorithm to construct a floor-plan for any n-node plane triangulation. In comparison with previous floor-planning algorithms in the literature, our solution is not only simpler in the algorithm itself, but also produces floor-plans which require fewer module types. An equally important aspect of our new algorithm lies in its ability to fit the floor-plan area in a rectangle of size (n-1)x(2n+1)/3. Lower bounds on the worst-case area for floor-planning any plane triangulation are also provided in the paper.Comment: 13 pages, 5 figures, An early version of this work was presented at 9th International Symposium on Graph Drawing (GD 2001), Vienna, Austria, September 2001. Accepted to Journal of Algorithms, 200

    On Visibility Representations of Non-planar Graphs

    Get PDF
    A rectangle visibility representation (RVR) of a graph consists of an assignment of axis-aligned rectangles to vertices such that for every edge there exists a horizontal or vertical line of sight between the rectangles assigned to its endpoints. Testing whether a graph has an RVR is known to be NP-hard. In this paper, we study the problem of finding an RVR under the assumption that an embedding in the plane of the input graph is fixed and we are looking for an RVR that reflects this embedding. We show that in this case the problem can be solved in polynomial time for general embedded graphs and in linear time for 1-plane graphs (i.e., embedded graphs having at most one crossing per edge). The linear time algorithm uses a precise list of forbidden configurations, which extends the set known for straight-line drawings of 1-plane graphs. These forbidden configurations can be tested for in linear time, and so in linear time we can test whether a 1-plane graph has an RVR and either compute such a representation or report a negative witness. Finally, we discuss some extensions of our study to the case when the embedding is not fixed but the RVR can have at most one crossing per edge

    Transforming planar graph drawings while maintaining height

    Full text link
    There are numerous styles of planar graph drawings, notably straight-line drawings, poly-line drawings, orthogonal graph drawings and visibility representations. In this note, we show that many of these drawings can be transformed from one style to another without changing the height of the drawing. We then give some applications of these transformations

    Time-Space Trade-Offs for Computing Euclidean Minimum Spanning Trees

    Full text link
    In the limited-workspace model, we assume that the input of size nn lies in a random access read-only memory. The output has to be reported sequentially, and it cannot be accessed or modified. In addition, there is a read-write workspace of O(s)O(s) words, where s{1,,n}s \in \{1, \dots, n\} is a given parameter. In a time-space trade-off, we are interested in how the running time of an algorithm improves as ss varies from 11 to nn. We present a time-space trade-off for computing the Euclidean minimum spanning tree (EMST) of a set VV of nn sites in the plane. We present an algorithm that computes EMST(V)(V) using O(n3logs/s2)O(n^3\log s /s^2) time and O(s)O(s) words of workspace. Our algorithm uses the fact that EMST(V)(V) is a subgraph of the bounded-degree relative neighborhood graph of VV, and applies Kruskal's MST algorithm on it. To achieve this with limited workspace, we introduce a compact representation of planar graphs, called an ss-net which allows us to manipulate its component structure during the execution of the algorithm

    Compact Visibility Representation of Plane Graphs

    Get PDF
    The visibility representation (VR for short) is a classical representation of plane graphs. It has various applications and has been extensively studied. A main focus of the study is to minimize the size of the VR. It is known that there exists a plane graph GG with nn vertices where any VR of GG requires a grid of size at least (2/3)n x((4/3)n-3) (width x height). For upper bounds, it is known that every plane graph has a VR with grid size at most (2/3)n x (2n-5), and a VR with grid size at most (n-1) x (4/3)n. It has been an open problem to find a VR with both height and width simultaneously bounded away from the trivial upper bounds (namely with size at most c_h n x c_w n with c_h < 1 and c_w < 2).Inthispaper,weprovidethefirstVRconstructionwiththisproperty.WeprovethateveryplanegraphofnverticeshasaVRwithheight<=max23/24n+2Ceil(sqrt(n))+4,11/12n+13andwidth<=23/12n.Thearea(heightxwidth)ofourVRislargerthantheareaofsomeofpreviousresults.However,boundingonedimensionoftheVRonlyrequiresfindingagoodstorientationoragooddualstorientationofG.Ontheotherhand,toboundbothdimensionsofVRsimultaneously,onemustfindagood). In this paper, we provide the first VR construction with this property. We prove that every plane graph of n vertices has a VR with height <= max{23/24 n + 2 Ceil(sqrt(n))+4, 11/12 n + 13} and width <= 23/12 n. The area (height x width) of our VR is larger than the area of some of previous results. However, bounding one dimension of the VR only requires finding a good st-orientation or a good dual s^*t^*-orientation of G. On the other hand, to bound both dimensions of VR simultaneously, one must find a good st$-orientation and a good dual s^*t^*-orientation at the same time, and thus is far more challenging. Since st-orientation is a very useful concept in other applications, this result may be of independent interests

    Grid Representations and the Chromatic Number

    Get PDF
    A grid drawing of a graph maps vertices to grid points and edges to line segments that avoid grid points representing other vertices. We show that there is a number of grid points that some line segment of an arbitrary grid drawing must intersect. This number is closely connected to the chromatic number. Second, we study how many columns we need to draw a graph in the grid, introducing some new \NP-complete problems. Finally, we show that any planar graph has a planar grid drawing where every line segment contains exactly two grid points. This result proves conjectures asked by David Flores-Pe\~naloza and Francisco Javier Zaragoza Martinez.Comment: 22 pages, 8 figure

    Bar 1-Visibility Drawings of 1-Planar Graphs

    Full text link
    A bar 1-visibility drawing of a graph GG is a drawing of GG where each vertex is drawn as a horizontal line segment called a bar, each edge is drawn as a vertical line segment where the vertical line segment representing an edge must connect the horizontal line segments representing the end vertices and a vertical line segment corresponding to an edge intersects at most one bar which is not an end point of the edge. A graph GG is bar 1-visible if GG has a bar 1-visibility drawing. A graph GG is 1-planar if GG has a drawing in a 2-dimensional plane such that an edge crosses at most one other edge. In this paper we give linear-time algorithms to find bar 1-visibility drawings of diagonal grid graphs and maximal outer 1-planar graphs. We also show that recursive quadrangle 1-planar graphs and pseudo double wheel 1-planar graphs are bar 1-visible graphs.Comment: 15 pages, 9 figure
    corecore