Consider a graph G with vertex set V in which each of the n vertices is assigned a number from the set {1, ..., k} for some positive integer k. This assignment phi is a labeling if all k numbers are used. If phi does not assign adjacent vertices the same label, then phi partitions V into k levels. In a level drawing, the y-coordinate of each vertex matches its label and the edges are drawn strictly y-monotone. This leads to level drawings in the xy-plane where all vertices with label j lie along the line lj = {(x, j) : x in Reals} and where each edge crosses any of the k horizontal lines lj for j in [1..k] at most once. A graph with such a labeling forms a level graph and is level planar if it has a level drawing without crossings.We first consider the class of level trees that are level planar regardless of their labeling. We call such trees unlabeled level planar (ULP). We describe which trees are ULP and provide linear-time level planar drawing algorithms for any labeling. We characterize ULP trees in terms of two forbidden subdivisions so that any other tree must contain a subtree homeomorphic to one of these. We also provide linear-time recognition algorithms for ULP trees. We then extend this characterization to all ULP graphs with five additional forbidden subdivisions, and provide linear-time recogntion and drawing algorithms for any given labeling.

Effective visualization of graphs is a powerful tool to help understand the relationships among the graph's underlying objects and to interact with them. Several styles for drawing graphs have emerged over the last three decades. Polyline drawing is a widely used style for drawing graphs, where each node is mapped to a distinct point in the plane and each edge is mapped to a polygonal chain between their corresponding nodes. Some common optimization criteria for such a drawing are defined in terms of area requirement, number of bends per edge, angular resolution, number of distinct line segments, edge crossings, and number of planar layers. In this thesis we develop algorithms for drawing graphs that optimize different aesthetic qualities of the drawing. Our algorithms seek to simultaneously optimize multiple drawing aesthetics, reveal potential trade-offs among them, and improve many previous graph drawing algorithms. We start by exploring probable trade-offs in the context of planar graphs. We prove that every $n$-vertex planar triangulation $G$ with maximum degree $\Delta$ can be drawn with at most $2n+t-3$ segments and $O(8^t \cdot \Delta^{2t})$ area, where $t$ is the number of leaves in a Schnyder tree of $G$. We then show that one can improve the area by allowing the edges to have bends. Since compact drawings often suffer from bad angular resolution, we seek to compute polyline drawings with better angular resolution. We develop a polyline drawing algorithm that is simple and intuitive, yet implies significant improvement over known results. At this point we move our attention to drawing nonplanar graphs. We prove that every thickness-$t$ graph can be drawn on $t$ planar layers with $\min\{O(2^{t/2} \cdot n^{1-1/\beta}), 2.25n +O(1)\}$ bends per edge, where $\beta = 2^{\lceil (t-2)/2 \rceil }$. Previously, the bend complexity, i.e., the number of bends per edge, was not known to be sublinear for $t>2$. We then examine the case when the number of available layers is restricted. The layers may now contain edge crossings. We develop a technique to draw complete graphs on two layers, which improves previous upper bounds on the number of edge crossings in such drawings. / October 2016

Un graphe est un objet mathématique modélisant des relations sur un ensemble d'éléments. Il est utilisé dans de nombreux domaines à des fins de modélisation. La taille et la complexité des graphes manipulés de nos jours entraînentdes besoins de visualisation afin de mieux les analyser. Dans cette thèse, nous présentons différents travaux en visualisation interactive de graphes qui s'attachent à exploiter les architectures de calcul parallèle (CPU et GPU) disponibles sur les stations de travail contemporaines. Un premier ensemble de travaux s'intéresse à des problématiques de dessin de graphes. Dessiner un graphe consiste à le plonger visuellement dans un plan ou un espace. La première contribution dans cette thématique est un algorithmede regroupement d'arêtes en faisceaux appelé Winding Roads.Cet algorithme intuitif, facilement implémentable et parallélisable permet de réduireconsidérablement les problèmes d'occlusion dans un dessin de graphedus aux nombreux croisements d'arêtes.La seconde contribution est une méthode permettant dedessiner un réseau métabolique complet. Ce type deréseau modélise l'ensemble des réactions biochimiquesse produisant dans les cellules d'un organise vivant.L'avantage de la méthode est de prendre en compte la décompositiondu réseau en sous-ensembles fonctionnels ainsi que de respecterles conventions de dessin biologique.Un second ensemble de travaux porte sur des techniques d'infographiepour la visualisation interactive de graphes. La première contribution dans cette thématique est une technique de rendude courbes paramétriques exploitant pleinement le processeur graphique. La seconde contribution est une méthodede rendu nommée Edge splatting permettant de visualiserla densité des faisceaux d'arêtes dans un dessin de grapheavec regroupement d'arêtes. La dernière contribution portesur des techniques permettant de mettre en évidence des sous-graphesd'intérêt dans le contexte global d'une visualisation de graphes. / A graph is a mathematical object used to model relations over a set of elements.It is used in numerous fields for modeling purposes. The size and complexityof graphs manipulated today call a need for visualization to better analyze them.In that thesis, we introducedifferent works in interactive graph visualisation which aim at exploiting parallel computing architectures (CPU and GPU) available on contemporary workstations.A first set of works focuses on graph drawing problems.Drawing a graph consists of embedding him in a plane or a space.The first contribution in that theme is an edge bundling algorithmnamed Winding Roads. That intuitive, easyly implementable and parallelizable algorithmallows to considerably reduce clutter due to numerous edge crossings in a graph drawing.The second contribution is a method to draw a complete metabolicnetwork. That kind of network models the whole set of biochemical reactionsoccurring within cells of a living organism. The advantage of the methodis to take into account the decomposition of the network into functionnal subsetsbut also to respect biological drawing conventions.A second set of works focuses on computer graphics techniquesfor interactive graph visualisation. The first contributionin that theme is a technique for rendering parametric curvesthat fully exploits the graphical processor unit. The second contributionis a rendering technique named Edge splatting that allowsto visualize the bundles densities in an edge bundled layout. Thelast contribution introduces some techniques for emphasizingsub-graphs of interest in the global context of a graph visualization.

<p>U sklopu doktorske disertacije izvršeno je istraživanje vezano za automatsko<br />raspoređivanje elemenata dijagrama. Kroz analizu postojećih rešenja uočen je<br />prostor za poboljšanja, posebno po pitanju raznovrsnosti dostupnih algoritama<br />i pomoći korisniku pri izboru najpogodnijeg od njih. U okviru istraživanja<br />proučavan, implementiran i u pojedinim slučajevima unapređen je širok<br />spektar algoritama za crtanje i analizu grafova. Definisan je postupak<br />automatskog izbora odgovarajućeg algoritma za raspoređivanje elemenata<br />grafova na osnovu njihovih osobina. Dodatno, osmišljen je jezik specifičan za<br />domen koji korisnicima grafičkih editora pruža pomoć u izboru algoritma za<br />raspoređivanje, a programerima brže pisanje koda za poziv željenog algoritma.</p> / <p>This thesis presents a research aimed towards the problem of automatically<br />laying out elements of a diagram. The analysis of existing solutions showed that there<br />is some room for improvement, especially regarding variety of available algorithms.<br />Also, none of the solutions offer possibility of automatically choosing an appropriate<br />graph layout algorithm. Within the research, a large number of different algorithms for<br />graph drawing and analysis were studied, implemented, and, in some cases,<br />enhanced. A method for automatically choosing the best available layout algorithm<br />based on properties of a graph was defined. Additionally, a domain-specific language<br />for specifying a graph&rsquo;s layout was designed.</p>

We can visualize a graph by producing a geometric representation of the graph in which each node is represented by a single point on the plane, and each edge is represented by a curve that connects its two endpoints. Directed graphs are often used to model hierarchical structures; in order to visualize the hierarchy represented by such a graph, it is desirable that a drawing of the graph reflects this hierarchy. This can be achieved by drawing all the edges in the graph such that they all point in an upwards direction. A graph that has a drawing in which all edges point in an upwards direction and in which no edges cross is known as an upward planar graph. Unfortunately, testing if a graph is upward planar is NP-complete. Parameterized complexity is a technique used to find efficient algorithms for hard problems, and in particular, NP-complete problems. The main idea is that the complexity of an algorithm can be constrained, for the most part, to a parameter that describes some aspect of the problem. If the parameter is fixed, the algorithm will run in polynomial time. In this thesis, we investigate contracting an edge in an upward planar graph that has a specified embedding, and show that we can determine whether or not the resulting embedding is upward planar given the orientation of the clockwise and counterclockwise neighbours of the given edge. Using this result, we then show that under certain conditions, we can join two upward planar graphs at a vertex and obtain a new upward planar graph. These two results expand on work done by Hutton and Lubiw. Finally, we show that a biconnected graph has at most <i>k</i>!8^<i>k</i>-1 planar embeddings, where <i>k</i> is the number of triconnected components. By using an algorithm by Bertolazzi et al. that tests whether a given embedding is upward planar, we obtain a parameterized algorithm, where the parameter is the number of triconnected components, for testing the upward planarity of a biconnected graph. This algorithm runs in <i>O</i>(<i>k</i>!8^<i>k</i><i>n</i>³) time.

We can visualize a graph by producing a geometric representation of the graph in which each node is represented by a single point on the plane, and each edge is represented by a curve that connects its two endpoints. Directed graphs are often used to model hierarchical structures; in order to visualize the hierarchy represented by such a graph, it is desirable that a drawing of the graph reflects this hierarchy. This can be achieved by drawing all the edges in the graph such that they all point in an upwards direction. A graph that has a drawing in which all edges point in an upwards direction and in which no edges cross is known as an upward planar graph. Unfortunately, testing if a graph is upward planar is NP-complete. Parameterized complexity is a technique used to find efficient algorithms for hard problems, and in particular, NP-complete problems. The main idea is that the complexity of an algorithm can be constrained, for the most part, to a parameter that describes some aspect of the problem. If the parameter is fixed, the algorithm will run in polynomial time. In this thesis, we investigate contracting an edge in an upward planar graph that has a specified embedding, and show that we can determine whether or not the resulting embedding is upward planar given the orientation of the clockwise and counterclockwise neighbours of the given edge. Using this result, we then show that under certain conditions, we can join two upward planar graphs at a vertex and obtain a new upward planar graph. These two results expand on work done by Hutton and Lubiw. Finally, we show that a biconnected graph has at most <i>k</i>!8^<i>k</i>-1 planar embeddings, where <i>k</i> is the number of triconnected components. By using an algorithm by Bertolazzi et al. that tests whether a given embedding is upward planar, we obtain a parameterized algorithm, where the parameter is the number of triconnected components, for testing the upward planarity of a biconnected graph. This algorithm runs in <i>O</i>(<i>k</i>!8^<i>k</i><i>n</i>³) time.

The one- and two-sided bipartite graph drawing problem alms to find a layout of a bipartite graph, with vertices of the two parts placed on parallel imaginary lines, that has the minimum number of edge-crossings. Vertices of one part are in fixed positions for the one-sided problem, whereas all vertices are free to move along their lines in the two-sided version. Many different heuristics exist for finding approximations to these problems, which are NP-hard. New sequential and parallel methods for producing drawings with low edgecrossings are investigated and compared to existing algorithms, notably Penalty Minimisation and Sifting, the current leaders. For the one-sided problem, new methods that include those based on simple stochastic hillclimbing, simulated annealing and genet.ic algorithms were tested. The new block-crossover genetic algorithm produced very good results with lower crossings than existing methods, although it tended to be slower. However, time was a secondary aim, the priority being to achieve low numbers of crossings. This algorithm can also be seeded with the output of an existing algorithm to improve results; combining with Penalty Minimisation in this way improved both the speed and number of crossings. Four parallel methods for the one-sided problem have been created, although two were abandoned because they gave bad results for even simple graphs. The other two methods, based on stochastic hill-climbing, produced acceptable results in faster times than similar sequential methods. PVM was used as the parallel communication system. Two new heuristics were studied for the two-sided problem, for which the only known existing method is to apply one-sided algorithms iteratively. The first is based on a heuristic for the linear arrangment problem; the second is a method of performing stochastic hill-climbing on two sides. A way of applying anyone-sided algorithm iteratively was also created. The linear arrangement method based on the Koren-Harel multi-scale algorithm achieved the best results, outperforming iterative Barycentre (previously the best method) and iterative Penalty Minimisation. Another area of this work created three new heuristics for the k-planar drawing problem where k > 1. These are the first known practical algorithms to solve this problem. A sequential genetic algorithm based on TimGA is devised to work on k-planar graphs. Two parallel algorithms, one island model and the other a 'mesh' model, are also given. Comparison of results for k = 2 indicate that the parallel island method is better than the other two methods. MPI was used for the parallel communication. Overall, 14 new methods are introduced, of which 10 were developed into working algorithms. For the one-sided bipartite graph drawing problem the new block-crossover genetic algorithm can produce drawings with lower crossings than the current best available algorithms. The parallel methods do not perform as well as the sequential ones, although they generally achieved the same results faster. All of the new two-sided methods worked well; the weighted two-sided swap stochastic hill-climbing method was comparable to the existing best method, iterative Barycentre, and generally produced drawings with lower crossings, although it suffered with needing a good termination condition. The new methods based on the linear arrangement problem consistently produced drawings with lower crossings than iterative Barycentre, although they were nearly always slower. A new parallel algorithm for the k-planar drawing problem, based on the island model, generally created drawings with the lowest edge-crossings, although no algorithms were known to exist to make comparisons.

Les graphes, outil mathématique pour modéliser les relations entre des entités, sont en augmentation constante du fait d'internet (par exemple les réseaux sociaux). La visualisation de graphe (aussi appelée dessin) permet d'obtenir immédiatement des informations sur le graphe. Les graphes issus d'internet sont généralement stockés de manière morcelée sur plusieurs machines connectées par un réseau. Cette thèse a pour but de développer des algorithmes de dessin de très grand graphes dans le paradigme MapReduce, utilisé pour le calcul sur cluster. Parmi les algorithmes de dessin, les algorithmes reposants sur un modèle physique sous-jacent pour réaliser le dessin permettent d'obtenir un bon dessin indépendamment de la nature du graphe. Nous proposons deux algorithmes par modèle de forces conçus dans le paradigme MapReduce. GDAD, le premier algorithme par modèle de force dans le paradigme MapReduce, utilise des pivots pour simplifier le calcul des interactions entre les nœuds du graphes. MuGDAD, le prolongement de GDAD, utilise une simplification récursive du graphe pour effectuer le dessin, toujours à l'aide de pivots. Nous comparons ces deux algorithmes avec les algorithmes de l'état de l'art pour évaluer leurs performances. / Graphs, usually used to model relations between entities, are continually growing mainly because of the internet (social networks for example). Graph visualization (also called drawing) is a fast way of collecting data about a graph. Internet graphs are often stored in a distributed manner, split between several machines interconnected. This thesis aims to develop drawing algorithms to draw very large graphs using the MapReduce paradigm, used for cluster computing. Among graph drawing algorithms, those which rely on a physical model to compute the node placement are generally considered to draw graphs well regardless of the type of graph. We developped two force-directed graph drawing algorithms in the MapReduce paradigm. GDAD, the fist distributed force-directed graph drawing algorithm ever, uses pivots to simplify computations of node interactions. MuGDAD, following GDAD, uses a recursive simplification to draw the original graph, keeping the pivots. We compare these two algorithms with the state of the art to assess their performances.

Dans cette thèse, nous présentons trois problèmes concernant les graphes planaires.Nous travaillons tout d'abord sur les dessins planaires non-alignés, c'est-à-dire des dessins planaires de graphes sur une grille sans que deux sommets se trouvent sur la même ligne ou la même colonne.Nous caractérisons les graphes planaires possédant un tel dessin sur une grille de taille $n times n$, et nous présentons deux algorithmes générant un dessin planaire non-aligné avec arêtes brisées sur cette grille pour tout graphe planaire, avec $n-3$ ou $min(frac{2n-3}{5},$ $#{text{triangles s{'e}parateurs}}+1)$ brisures au total.Nous proposons également deux algorithmes dessinant un dessin planaire non-aligné sur des grilles d'aire $O(n^4)$. Nous donnons des résultats spécifiques concernant les graphes 4-connexes et de type triangle-emboîté.Le second sujet de cette thèse est la domination de puissance dans les graphes planaires. Nous exhibons une famille de graphes ayant un nombre de domination de puissance $gamma_P$ au moins égal à $frac{n}{6}$. Nous montrons aussi que pour tout graphe planaire maximal $G$ à $n geq 6$ sommets, $gamma_P(G) leq frac{n-2}{4}$. Enfin, nous étudions les grilles triangulaires $T_k$ à bord hexagonal de dimension $k$ et nous montrons que $frac{k}{3} - frac{1}{6} leq gamma_P(T_k) leq lceil frac{k}{3} rceil$.Nous étudions également l'énumération des orientations planaires Eulériennes. Nous proposons une nouvelle décomposition de ces cartes. En considérant les orientations des dernières $2k-1$ arêtes autour de la racine, nous définissons des sous- et sur-ensembles des orientations planaires Eulériennes paramétrés par $k$.Pour chaque classe, nous proposons un système d'équations fonctionnelles définissant leur série génératrice, et nous prouvons que celle-ci est toujours algébrique. Nous montrons ainsi que la constance de croissance des orientations planaires Eulériennes est entre 11.56 et 13.005. / In this thesis, we present results on three different problems concerning planar graphs.We first give some new results on planar non-aligned drawings, i.e. planar grid drawings where vertices are all on different rows and columns.We show that not every planar graph has a non-aligned drawing on an $n times n$-grid, but we present two algorithms generating a non-aligned polyline drawings on such a grid requiring either $n-3$ or $min(frac{2n-3}{5},$ $#{text{separating triangles}}+1)$ bends in total.Concerning non-minimal grids, we give two algorithms drawing a planar non-aligned drawing on grids with area of order $n^4$. We also give specific results for 4-connected graphs and nested-triangle graphs.The second topic is power domination in planar graphs. We present a family of graphs with power dominating number $gamma_P$ at least $frac{n}{6}$. We then prove that for every maximal planar graph $G$ of order $n$, $gamma_P(G) leq frac{n-2}{4}$, and we give a constructive algorithm.We also prove that for triangular grids $T_k$ of dimension $k$ with hexagonal-shape border, $frac{k}{3} - frac{1}{6} leq gamma_P(T_k) leq lceil frac{k}{3} rceil$.Finally, we focus on the enumeration of planar Eulerian orientations. After proposing a new decomposition for these maps, we define subsets and supersets of planar Eulerian orientations with parameter $k$, generated by looking at the orientations of the last $2k-1$ edges around the root vertex.For each set, we give a system of functional equations defining its generating function, and we prove that it is always algebraic.This way, we show that the growth rate of planar Eulerian orientations is between 11.56 and 13.005.

Finding a visually pleasing layout from a set of vertices and edges is the goal of automatic graph drawing. A requirement that has been barely explored however, is that users would like to specify portions of their layouts that are not altered by such algorithms. For example the user may have put a lot of manual effort into fixing a portion of a large layout and, while they would like an automatic layout applied to most of the layout, they do not want their work undone on the portion they manually fixed earlier. CluStic, the system developed and evaluated in this thesis, provides this capability. CluStic maintain the internal structure of a cluster by giving it priority over other elements in the graph. After high priority element has been positioned, non-priority vertices may be placed at the most appropriate remaining positions. Furthermore CluStic produces layouts which also maintain common aesthetic criteria: edge crossing minimization, layout height and edge straightening. Our method in this thesis is to first conduct an initial exploration study where we cross compare four industrial tools: Cytogate, GraphDraw, Diagram.Net and GraphNet. A set of layouts are generated with these tools and the user is timed on a task to identify the longest path. Through this exploration study we develop out intuition and determined that Cytogate is the best performing tool for longest path identification. Given this experience we fully develop CluStic and conduct our main study where we cross compare it with Cytogate and a baseline Breadth-first Search algorithm. Results show that CluStic produces drawings of good quality, Clustic achieves a visualization efficiency score of 1,4 which is an increase compared to the BFS layout (-3,8). CluStic is outperformed by Cytogate which achieves a visualization efficiency score of 1,9 and therefore produces less visually pleasing drawings. However Clustic, unlike Cytogate can preserve initial static structures, thus when a graph contains elements in which their position cannot be altered CluStic is a better choice. / Målet med automatiserad grafritning är att utifrån en uppsättning noder och kanter hitta en layout som är visuellt tillfredställande. Ett delområde som inte utforskats nog är möjligheten till att låsa vissa komponenter i grafen som sedan inte får alterneras av grafritningsalgoritmen. En användare som exempel, strukturerar vissa delar av grafen manuellt och applicerar sedan automatisk layout av resterande element utan att förstöra den struktur som manuellt skapats. CluStic, grafritningsverktyget som skapats och utvärderats i denna masters uppsats fyller denna funktion. CluStic bevarar den interna strukturen för ett kluster genom att tilldela en högre prioritet för noder i klustret med avseende på övriga element i grafen. Efter att högprioritets element placerats tilldelas resterande element sina bäst tillgängliga positioner. Utöver detta så uppfyller CluStic några av de vanligaste estetiska mål inom grafritning: minimera antalet kantkorsningar, minimera höjden, och räta ut kanter. Metoden som används i denna master uppsatts var att först gör en inledande studie där vi undersöker fyra populära grafritnings verktyg: Cytogate, GraphDraw, Diagram.Net och GraphNet. En uppsättning grafer genereras av dessa verktyg och vi mäter hur lång tid det tar för en användare att hitta den längsta vägen i grafen. Genom denna studie konstaterar vi att Cytogate presenterade grafer med best kvalitet. Från kunskap samlad i den inledande studien utvecklar vi CluStic och utför uppsatsens huvud studie där vi jämför CluStic med avseende på Cytogate och en bas layout Breddenförst algoritm. CluStic uppnår ett visualiserings effektivitetsvärde på 1,4 vilket är en ökning jämtemot Bredden-först algoritmen (-3,8). CluStic levererar inte layouter som är mer visuellt tillfredställande än de som skapats av Cytogate som får ett visualiserings effektivitetsvärde på 1,9. CluStic tillskillnad från Cytogate bevarar den internt fixa strukturen mellan element med hög prioritet vilket gör CluStic till det bättre verktyget för grafer med statiska element.