On Star and Caterpillar Arboricity
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Linear K-Arboricities on Trees
Discrete Applied Mathematics 103 (2000) 281–287 View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by Elsevier - Publisher Connector Note Linear k-arboricities on trees Gerard J. Changa; 1, Bor-Liang Chenb, Hung-Lin Fua, Kuo-Ching Huangc; ∗;2 aDepartment of Applied Mathematics, National Chiao Tung University, Hsinchu 300, Taiwan bDepartment of Business Administration, National Taichung Institue of Commerce, Taichung 404, Taiwan cDepartment of Applied Mathematics, Providence University, Shalu 433, Taichung, Taiwan Received 31 October 1997; revised 15 November 1999; accepted 22 November 1999 Abstract For a ÿxed positive integer k, the linear k-arboricity lak (G) of a graph G is the minimum number ‘ such that the edge set E(G) can be partitioned into ‘ disjoint sets and that each induces a subgraph whose components are paths of lengths at most k. This paper studies linear k-arboricity from an algorithmic point of view. In particular, we present a linear-time algo- rithm to determine whether a tree T has lak (T)6m. ? 2000 Elsevier Science B.V. All rights reserved. Keywords: Linear forest; Linear k-forest; Linear arboricity; Linear k-arboricity; Tree; Leaf; Penultimate vertex; Algorithm; NP-complete 1. Introduction All graphs in this paper are simple, i.e., ÿnite, undirected, loopless, and without multiple edges. A linear k-forest is a graph whose components are paths of length at most k.Alinear k-forest partition of G is a partition of the edge set E(G) into linear k-forests. The linear k-arboricity of G, denoted by lak (G), is the minimum size of a linear k-forest partition of G. -
Orienting Fully Dynamic Graphs with Worst-Case Time Bounds⋆
Orienting Fully Dynamic Graphs with Worst-Case Time Bounds? Tsvi Kopelowitz1??, Robert Krauthgamer2 ???, Ely Porat3, and Shay Solomon4y 1 University of Michigan, [email protected] 2 Weizmann Institute of Science, [email protected] 3 Bar-Ilan University, [email protected] 4 Weizmann Institute of Science, [email protected] Abstract. In edge orientations, the goal is usually to orient (direct) the edges of an undirected network (modeled by a graph) such that all out- degrees are bounded. When the network is fully dynamic, i.e., admits edge insertions and deletions, we wish to maintain such an orientation while keeping a tab on the update time. Low out-degree orientations turned out to be a surprisingly useful tool for managing networks. Brodal and Fagerberg (1999) initiated the study of the edge orientation problem in terms of the graph's arboricity, which is very natural in this context. Their solution achieves a constant out-degree and a logarithmic amortized update time for all graphs with constant arboricity, which include all planar and excluded-minor graphs. It remained an open ques- tion { first proposed by Brodal and Fagerberg, later by Erickson and others { to obtain similar bounds with worst-case update time. We address this 15 year old question by providing a simple algorithm with worst-case bounds that nearly match the previous amortized bounds. Our algorithm is based on a new approach of maintaining a combina- torial invariant, and achieves a logarithmic out-degree with logarithmic worst-case update times. This result has applications to various dynamic network problems such as maintaining a maximal matching, where we obtain logarithmic worst-case update time compared to a similar amor- tized update time of Neiman and Solomon (2013). -
A Note on Soenergy of Stars, Bi-Stars and Double Star Graphs
BULLETIN OF THE INTERNATIONAL MATHEMATICAL VIRTUAL INSTITUTE ISSN (p) 2303-4874, ISSN (o) 2303-4955 www.imvibl.org /JOURNALS / BULLETIN Vol. 6(2016), 105-113 Former BULLETIN OF THE SOCIETY OF MATHEMATICIANS BANJA LUKA ISSN 0354-5792 (o), ISSN 1986-521X (p) A NOTE ON soENERGY OF STARS, BISTAR AND DOUBLE STAR GRAPHS S. P. Jeyakokila and P. Sumathi Abstract. Let G be a finite non trivial connected graph.In the earlier paper idegree, odegree, oidegree of a minimal dominating set of G were introduced, oEnergy of a graph with respect to the minimal dominating set was calculated in terms of idegree and odegree. Algorithm to get the soEnergy was also introduced and soEnergy was calculated for some standard graphs in the earlier papers. In this paper soEnergy of stars, bistars and double stars with respect to the given dominating set are found out. 1. INTRODUCTION Let G = (V; E) be a finite non trivial connected graph. A set D ⊂ V is a dominating set of G if every vertex in V − D is adjacent to some vertex in D.A dominating set D of G is called a minimal dominating set if no proper subset of D is a dominating set. Star graph is a tree consisting of one vertex adjacent to all the others. Bistar is a graph obtained from K2 by joining n pendent edges to both the ends of K2. Double star is the graph obtained from K2 by joining m pendent edges to one end and n pendent edges to the other end of K2. -
Faster Sublinear Approximation of the Number of K-Cliques in Low-Arboricity Graphs
Faster sublinear approximation of the number of k-cliques in low-arboricity graphs Talya Eden ✯ Dana Ron ❸ C. Seshadhri ❹ Abstract science [10, 49, 40, 58, 7], with a wide variety of applica- Given query access to an undirected graph G, we consider tions [37, 13, 53, 18, 44, 8, 6, 31, 54, 38, 27, 57, 30, 39]. the problem of computing a (1 ε)-approximation of the This problem has seen a resurgence of interest because number of k-cliques in G. The± standard query model for general graphs allows for degree queries, neighbor queries, of its importance in analyzing massive real-world graphs and pair queries. Let n be the number of vertices, m be (like social networks and biological networks). There the number of edges, and nk be the number of k-cliques. are a number of clever algorithms for exactly counting Previous work by Eden, Ron and Seshadhri (STOC 2018) ∗ n mk/2 k-cliques using matrix multiplications [49, 26] or combi- gives an O ( 1 + )-time algorithm for this problem n /k nk k natorial methods [58]. However, the complexity of these (we use O∗( ) to suppress poly(log n, 1/ε,kk) dependencies). algorithms grows with mΘ(k), where m is the number of · Moreover, this bound is nearly optimal when the expression edges in the graph. is sublinear in the size of the graph. Our motivation is to circumvent this lower bound, by A line of recent work has considered this question parameterizing the complexity in terms of graph arboricity. from a sublinear approximation perspective [20, 24]. -
Total Chromatic Number of Star and Bistargraphs 1D
International Journal of Pure and Applied Mathematics Volume 117 No. 21 2017, 699-708 ISSN: 1311-8080 (printed version); ISSN: 1314-3395 (on-line version) url: http://www.ijpam.eu Special Issue ijpam.eu Total Chromatic Number of Star and BistarGraphs 1D. Muthuramakrishnanand 2G. Jayaraman 1Department of Mathematics, National College, Trichy, Tamil Nadu, India. [email protected] 2Research Scholar, National College, Trichy, Tamil Nadu, India. [email protected] Abstract A total coloring of a graph G is an assignment of colors to both the vertices and edges of G, such that no two adjacent or incident vertices and edges of G are assigned the same colors. In this paper, we have discussed 2 the total coloring of 푀 퐾1,푛 , 푇 퐾1,푛 , 퐿 퐾1,푛 and 퐵푛,푛and we obtained the 2 total chromatic number of 푀 퐾1,푛 , 푇 퐾1,푛 , 퐿 퐾1,푛 and 퐵푛,푛. AMS Subject Classification: 05C15 Keywords and Phrases:Middle graph, line graph, total graph, star graph, square graph, total coloring and total chromatic number. 699 International Journal of Pure and Applied Mathematics Special Issue 1. Introduction In this paper, we have chosen finite, simple and undirected graphs. Let퐺 = (푉 퐺 , 퐸 퐺 ) be a graph with the vertex set 푉(퐺) and the edge set E(퐺), respectively. In 1965, the concept of total coloring was introduced by Behzad [1] and in 1967 he [2] came out new ideology that, the total chromatic number of complete graph and complete bi-partite graph. A total coloring of퐺, is a function 푓: 푆 → 퐶, where 푆 = 푉 퐺 ∪ 퐸 퐺 and C is a set of colors to satisfies the given conditions. -
Parameterized Algorithms for Recognizing Monopolar and 2
Parameterized Algorithms for Recognizing Monopolar and 2-Subcolorable Graphs∗ Iyad Kanj1, Christian Komusiewicz2, Manuel Sorge3, and Erik Jan van Leeuwen4 1School of Computing, DePaul University, Chicago, USA, [email protected] 2Institut für Informatik, Friedrich-Schiller-Universität Jena, Germany, [email protected] 3Institut für Softwaretechnik und Theoretische Informatik, TU Berlin, Germany, [email protected] 4Max-Planck-Institut für Informatik, Saarland Informatics Campus, Saarbrücken, Germany, [email protected] October 16, 2018 Abstract A graph G is a (ΠA, ΠB)-graph if V (G) can be bipartitioned into A and B such that G[A] satisfies property ΠA and G[B] satisfies property ΠB. The (ΠA, ΠB)-Recognition problem is to recognize whether a given graph is a (ΠA, ΠB )-graph. There are many (ΠA, ΠB)-Recognition problems, in- cluding the recognition problems for bipartite, split, and unipolar graphs. We present efficient algorithms for many cases of (ΠA, ΠB)-Recognition based on a technique which we dub inductive recognition. In particular, we give fixed-parameter algorithms for two NP-hard (ΠA, ΠB)-Recognition problems, Monopolar Recognition and 2-Subcoloring, parameter- ized by the number of maximal cliques in G[A]. We complement our algo- rithmic results with several hardness results for (ΠA, ΠB )-Recognition. arXiv:1702.04322v2 [cs.CC] 4 Jan 2018 1 Introduction A (ΠA, ΠB)-graph, for graph properties ΠA, ΠB , is a graph G = (V, E) for which V admits a partition into two sets A, B such that G[A] satisfies ΠA and G[B] satisfies ΠB. There is an abundance of (ΠA, ΠB )-graph classes, and important ones include bipartite graphs (which admit a partition into two independent ∗A preliminary version of this paper appeared in SWAT 2016, volume 53 of LIPIcs, pages 14:1–14:14. -
Achromatic Coloring on Double Star Graph Families
International J.Math. Combin. Vol.3 (2009), 71-81 Achromatic Coloring on Double Star Graph Families Vernold Vivin J. Department of Mathematics, Sri Shakthi Institute of Engineering and Technology, Coimbatore - 641 062, Tamil Nadu, India. E-mail: vernold [email protected], [email protected] Venkatachalam M. Department of Mathematics, SSK College of Engineering and Technology, Coimbatore - 641 105, Tamil Nadu, India. E-mail: [email protected] Akbar Ali M.M. Department of Mathematics, Sri Shakthi Institute of Engineering and Technology, Coimbatore - 641 062, Tamil Nadu, India. E-mail: um [email protected] Abstract: The purpose of this article is to find the achromatic number, i.e., Smarandachely achromatic 1-coloring for the central graph, middle graph, total graph and line graph of double star graph K1,n,n denoted by C(K1,n,n), M(K1,n,n), T (K1,n,n) and L(K1,n,n) re- spectively. Keywords: Smarandachely achromatic k-coloring, Smarandachely achromatic number, central graph, middle graph, total graph, line graph and achromatic coloring. AMS(2000): 05C15 §1. Preliminaries For a given graph G = (V, E) we do an operation on G, by subdividing each edge exactly once and joining all the non adjacent vertices of G. The graph obtained by this process is called central graph [10] of G denoted by C(G). Let G be a graph with vertex set V (G) and edge set E(G). The middle graph [4] of G, denoted by M(G) is defined as follows. The vertex set of M(G) is V (G) E(G). Two vertices ∪ x, y in the vertex set of M(G) are adjacent in M(G) in case one of the following holds: (i) x, y are in E(G) and x, y are adjacent in G. -
Even Star Decomposition of Complete Bipartite Graphs
Journal of Mathematics Research; Vol. 8, No. 5; October 2016 ISSN 1916-9795 E-ISSN 1916-9809 Published by Canadian Center of Science and Education Even Star Decomposition of Complete Bipartite Graphs E. Ebin Raja Merly1 & J. Suthiesh Goldy2 1 Nesamony Memorial Christian college, Marthandam, KanyakumarI District, Tamilnadu-629165, India 2 Research scholar, Nesamony Memorial Christian college, Marthandam, Kanyakumari District, Tamilnadu-629165, India Correspondence: J. Suthiesh Goldy, Research Scholar, Nesamony Memorial Christian college, Marthandam, KanyakumarI District, Tamilnadu-629165, India. Email: [email protected] Received: August 24, 2016 Accepted: September 5, 2016 Online Published: September 27, 2016 doi:10.5539/jmr.v8n5p101 URL: http://dx.doi.org/10.5539/jmr.v8n5p101 Abstract A decomposition (G1, G2, G3, , Gn) of a graph G is an Arithmetic Decomposition(AD) if |E(G i)| = a + (i – 1)d for all i = 1, 2, , n and a, d Z+. Clearly q = n [2a + (n – 1)d]. The AD is a CMD if a = 1 and d = 1. In this paper we 2 introduced the new concept Even Decomposition of graphs. If a = 2 and d = 2 in AD, then q = n(n + 1). That is, the number of edges of G is the sum of first n even numbers 2, 4, 6, , 2n. Thus we call the AD with a = 2 and d = 2 as Even Decomposition. Since the number of edges of each subgraph of G is even, we denote the Even Decomposition as (G2, G4, , G2n). Keywords: Continuous Monotonic Decomposition, Decomposition of graph, Even Decomposition, Even Star Decomposition (ESD) 1. Introduction All basic terminologies from Graph Theory are used in this paper in the sense of Frank Harary. -
Star Arboricity
COMBINATORICA COMBINATORICA12 (4) (1992) 375-380 Akad~miai Kiadd - Springer-Verlag STAR ARBORICITY NOGA ALON, COLIN McDIARMID and BRUCE REED Received September 11, 1989 A star forest is a forest all of whose components are stars. The star arboricity, st(G) of a graph G is the minimum number of star forests whose union covers all the edges of G. The arboricity, A(G), of a graph G is the minimum number of forests whose union covers all the edges of G. Clearly st(G) > A(G). In fact, Algor and Alon have given examples which show that in some cases st(G) can be as large as A(G)+ f~(log/k) (where s is the maximum degree of a vertex in G). We show that for any graph G, st(G) <_A(G) + O(log ~). 1. Introduction All graphs considered here are finite and simple. For a graph H, let E(H) denote the set of its edges, and let V(H) denote the set of its vertices. A star is a tree with at most one vertex whose degree is not one. A star forest is a forest whose connected components are stars. The star arboricity of a graph G, denoted st(G), is the minimum number of star forests whose union covers all edges of G. The arboricity of G, denoted A(G) is the minimum number of forests needed to cover all edges of G. Clearly, st(G) > A(G) by definition. Furthermore, it is easy to see that any tree can be covered by two star forests. -
Star Coloring Outerplanar Bipartite Graphs
Discussiones Mathematicae Graph Theory 39 (2019) 899–908 doi:10.7151/dmgt.2109 STAR COLORING OUTERPLANAR BIPARTITE GRAPHS Radhika Ramamurthi and Gina Sanders Department of Mathematics California State University San Marcos San Marcos, CA 92096-0001 USA e-mail: [email protected] Abstract A proper coloring of the vertices of a graph is called a star coloring if at least three colors are used on every 4-vertex path. We show that all outerplanar bipartite graphs can be star colored using only five colors and construct the smallest known example that requires five colors. Keywords: chromatic number, star coloring, outerplanar bipartite graph. 2010 Mathematics Subject Classification: 05C15. 1. Introduction A proper r-coloring of a graph G is an assignment of labels from {1, 2,...,r} to the vertices of G so that adjacent vertices receive distinct colors. The minimum r so that G has a proper r-coloring is called the chromatic number of G, denoted by χ(G). The chromatic number is one of the most studied parameters in graph theory, and by convention, the term coloring of a graph is usually used instead of proper coloring. In 1973, Gr¨unbaum [5] considered proper colorings with the additional constraint that the subgraph induced by every pair of color classes is acyclic, i.e., contains no cycles. He called such colorings acyclic colorings, and the minimum r such that G has an acyclic r-coloring is called the acyclic chromatic number of G, denoted by a(G). In introducing the notion of an acyclic coloring, Gr¨unbaum noted that the condition that the union of any two color classes induces a forest can be generalized to other bipartite graphs. -
Sub-Coloring and Hypo-Coloring Interval Graphs⋆
Sub-coloring and Hypo-coloring Interval Graphs? Rajiv Gandhi1, Bradford Greening, Jr.1, Sriram Pemmaraju2, and Rajiv Raman3 1 Department of Computer Science, Rutgers University-Camden, Camden, NJ 08102. E-mail: [email protected]. 2 Department of Computer Science, University of Iowa, Iowa City, Iowa 52242. E-mail: [email protected]. 3 Max-Planck Institute for Informatik, Saarbr¨ucken, Germany. E-mail: [email protected]. Abstract. In this paper, we study the sub-coloring and hypo-coloring problems on interval graphs. These problems have applications in job scheduling and distributed computing and can be used as “subroutines” for other combinatorial optimization problems. In the sub-coloring problem, given a graph G, we want to partition the vertices of G into minimum number of sub-color classes, where each sub-color class induces a union of disjoint cliques in G. In the hypo-coloring problem, given a graph G, and integral weights on vertices, we want to find a partition of the vertices of G into sub-color classes such that the sum of the weights of the heaviest cliques in each sub-color class is minimized. We present a “forbidden subgraph” characterization of graphs with sub-chromatic number k and use this to derive a a 3-approximation algorithm for sub-coloring interval graphs. For the hypo-coloring problem on interval graphs, we first show that it is NP-complete and then via reduction to the max-coloring problem, show how to obtain an O(log n)-approximation algorithm for it. 1 Introduction Given a graph G = (V, E), a k-sub-coloring of G is a partition of V into sub-color classes V1,V2,...,Vk; a subset Vi ⊆ V is called a sub-color class if it induces a union of disjoint cliques in G. -
Branchwidth of Graphic Matroids
Branchwidth of graphic matroids. Fr´ed´eric Mazoit∗ and St´ephan Thomass´e† Abstract Answering a question of Geelen, Gerards, Robertson and Whittle [1], we prove that the branchwidth of a bridgeless graph is equal to the branch- width of its cycle matroid. Our proof is based on branch-decompositions of hypergraphs. By matroid duality, a direct corollary of this result is that the branchwidth of a bridgeless planar graph is equal to the branchwidth of its planar dual. This consequence was a direct corollary of a result by Seymour and Thomas [4]. 1 Introduction. The notion of branchwidth was introduced by Robertson and Seymour in their seminal paper Graph Minors X [3]. Very roughly speaking, the goal is to decom- pose a structure S along a tree T in such a way that subsets of S corresponding to disjoint branches of T are pairwise as disjoint as possible. One can define the branchwidth of various structures like graphs, hypergraphs, matroids, sub- modular functions... Our goal in this paper is to prove that the definitions of branchwidth for graphs and matroids coincide in the sense that the branchwidth of a bridgeless graph is equal to the branchwidth of its cycle matroid. Let us now define properly what these definitions are. Let H = (V, E) be a graph, or a hypergraph, and (E1,E2) be a partition of E. The border of (E1,E2) is the set of vertices δ(E1,E2) which belong to both an edge of E1 and an edge of E2. We write it δ(E1,E2), or simply δ(E1).