Graph Labeling Problems Appropriate for Undergraduate Research Cindy Wyels CSU Channel Islands Research with Undergraduates Session MathFest, 2009.

Slides:



Advertisements
Similar presentations
Coloring Warm-Up. A graph is 2-colorable iff it has no odd length cycles 1: If G has an odd-length cycle then G is not 2- colorable Proof: Let v 0, …,
Advertisements

Definitions Distance Diameter Radio Labeling Span Radio Number Gear Graph.
Radio Labeling of Ladder Graphs Josefina Flores Kathleen Lewis From: California State University Channel Islands Advisors: Dr. Tomova and Dr.Wyels Funding:
CS138A Single Source Shortest Paths Peter Schröder.
The Theory of NP-Completeness
From Rainbow to the Lonely Runner Daphne Liu Department of Mathematics California State Univ., Los Angeles January 24, 2007.
Edge-Coloring of Graphs On the left we see a 1- factorization of  5, the five-sided prism. Each factor is respresented by its own color. No edges of the.
Approximation Algorithms Chapter 5: k-center. Overview n Main issue: Parametric pruning –Technique for approximation algorithms n 2-approx. algorithm.
GOLOMB RULERS AND GRACEFUL GRAPHS
Last time: terminology reminder w Simple graph Vertex = node Edge Degree Weight Neighbours Complete Dual Bipartite Planar Cycle Tree Path Circuit Components.
Investigating properties of Kneser Graphs Modesty Briggs California State University, Northridge Sponsored by JPL/NASA Pair program; Funded by NSA and.
Interconnect Estimation without Packing via ACG Floorplans Jia Wang and Hai Zhou Electrical & Computer Engineering Northwestern University U.S.A.
Definition Hamiltonian graph: A graph with a spanning cycle (also called a Hamiltonian cycle). Hamiltonian graph Hamiltonian cycle.
Greedy Algorithms Reading Material: Chapter 8 (Except Section 8.5)
Lower Bounds for the Ropelength of Reduced Knot Diagrams by: Robert McGuigan.
Lower Bounds on the Distortion of Embedding Finite Metric Spaces in Graphs Y. Rabinovich R. Raz DCG 19 (1998) Iris Reinbacher COMP 670P
Graphs: Graceful, Equitable and Distance Labelings
Tirgul 13. Unweighted Graphs Wishful Thinking – you decide to go to work on your sun-tan in ‘ Hatzuk ’ beach in Tel-Aviv. Therefore, you take your swimming.
Greedy Algorithms Like dynamic programming algorithms, greedy algorithms are usually designed to solve optimization problems Unlike dynamic programming.
Cover Pebbling Cycles and Graham’s Conjecture Victor M. Moreno California State University Channel Islands Advisor: Dr. Cynthia Wyels Sponsored by the.
Seminar in Computer Science 1 Two-Dimensional Patterns with Distinct Differences – Construction, Bounds, and Maximal Anticodes COMPUTER SCIENCE.
Antimagic Labellings of Graphs Torsten Mütze Joint work with Dan Hefetz and Justus Schwartz.
Radio Labeling Cartesian Products of Path Graphs Eduardo Calles and Henry Gómez Advisors: Drs. Maggy Tomova and Cindy Wyels Funding: NSF, NSA, and Moody’s,
TECH Computer Science Graph Optimization Problems and Greedy Algorithms Greedy Algorithms  // Make the best choice now! Optimization Problems  Minimizing.
Open Problems in Exclusive Sum Labeling Mirka Miller, Joe Ryan, Slamin, Kiki Sugeng, Mauritsius Tuga School of Computer Science and Software Engineering.
The Theory of NP-Completeness 1. Nondeterministic algorithms A nondeterminstic algorithm consists of phase 1: guessing phase 2: checking If the checking.
1 The Theory of NP-Completeness 2012/11/6 P: the class of problems which can be solved by a deterministic polynomial algorithm. NP : the class of decision.
Minimal Fault Diameter for Highly Resilient Product Networks Khaled Day, Abdel-Elah Al-Ayyoub IEEE Trans. On Parallel and Distributed Systems 2000 vol.
The Complexity of Optimization Problems. Summary -Complexity of algorithms and problems -Complexity classes: P and NP -Reducibility -Karp reducibility.
Trees and Distance. 2.1 Basic properties Acyclic : a graph with no cycle Forest : acyclic graph Tree : connected acyclic graph Leaf : a vertex of degree.
Graph Pegging By Jason Counihan. The Rules of Pegging We start with a graph, such as this graph representation a cube. –Graphs are made of vertices (dots)
Boundary vertices in graphs Discrete Mathematics 263 (2003) Gary Chartrand, David Erwin Garry L. Johns, Ping Zhang.
Copyright © Zeph Grunschlag, More on Graphs.
On a Network Creation Game PoA Seminar Presenting: Oren Gilon Based on an article by Fabrikant et al 1.
1 Combinatorial Algorithms Parametric Pruning. 2 Metric k-center Given a complete undirected graph G = (V, E) with nonnegative edge costs satisfying the.
1 Multicasting in a Class of Multicast-Capable WDM Networks From: Y. Wang and Y. Yang, Journal of Lightwave Technology, vol. 20, No. 3, Mar From:
CSE 589 Part VI. Reading Skiena, Sections 5.5 and 6.8 CLR, chapter 37.
The length of vertex pursuit games Anthony Bonato Ryerson University CCC 2013.
Lecture 6 NP Class. P = ? NP = ? PSPACE They are central problems in computational complexity.
Graph Theory and Applications
Mutually independent Hamiltonian cycles on Cartesian product graphs Student: Kai-Siou Wu ( 吳凱修 ) Adviser: Justie Su-Tzu Juan 1National Chi Nan University.
The L(2,1)-labelling of Ping An, Yinglie Jin, Nankai University.
Graphs Lecture 2. Graphs (1) An undirected graph is a triple (V, E, Y), where V and E are finite sets and Y:E g{X V :| X |=2}. A directed graph or digraph.
Copyright (c) by Daphne Liu and Melanie Xie Radio Numbers for Square Paths & Cycles Daphne Liu & Melanie Xie California State University, Los Angeles Department.
Lecture 25 NP Class. P = ? NP = ? PSPACE They are central problems in computational complexity.
1 On Channel Assignment Of Graphs Author : Hsin-Ju Wu Adviser : Yung-Ling Lai Speaker : Shr-Jia Hung.
Suppose G = (V, E) is a directed network. Each edge (i,j) in E has an associated ‘length’ c ij (cost, time, distance, …). Determine a path of shortest.
Indian Institute of Technology Kharagpur PALLAB DASGUPTA Graph Theory: Trees Pallab Dasgupta, Professor, Dept. of Computer Sc. and Engineering, IIT
NOTE: To change the image on this slide, select the picture and delete it. Then click the Pictures icon in the placeholder to insert your own image. Fast.
The Theory of NP-Completeness 1. Nondeterministic algorithms A nondeterminstic algorithm consists of phase 1: guessing phase 2: checking If the checking.
Eternal Domination Chip Klostermeyer.
1 The Theory of NP-Completeness 2 Review: Finding lower bound by problem transformation Problem X reduces to problem Y (X  Y ) iff X can be solved by.
Trees.
ICS 353: Design and Analysis of Algorithms NP-Complete Problems King Fahd University of Petroleum & Minerals Information & Computer Science Department.
The Theory of NP-Completeness
Graph Coloring.
Introduction to the Design and Analysis of Algorithms
Graphs Hubert Chan (Chapter 9) [O1 Abstract Concepts]
Lecture 2-2 NP Class.
COMP 6/4030 ALGORITHMS Prim’s Theorem 10/26/2000.
Adjacency labeling schemes and induced-universal graphs
ICS 353: Design and Analysis of Algorithms
Graph Theory Graph Colorings.
Graph Operations And Representation
Trees.
Introduction Wireless Ad-Hoc Network
Approximation Algorithms
Miniconference on the Mathematics of Computation
The Theory of NP-Completeness
Locality In Distributed Graph Algorithms
Presentation transcript:

Graph Labeling Problems Appropriate for Undergraduate Research Cindy Wyels CSU Channel Islands Research with Undergraduates Session MathFest, 2009

Overview Distance labeling schemes Distance labeling schemes Radio labeling Radio labeling Research with undergrads: context Research with undergrads: context Problems for undergraduate research Problems for undergraduate research  Radio numbers of graph families  Radio numbers and graph properties  Properties of radio numbers  Radio numbers and graph operations  Achievable radio numbers

Distance Labeling Motivating Context: the Channel Assignment Problem General Idea: geographically close transmitters must be assigned channels with large frequency differences; distant transmitters may be assigned channels with relatively close frequencies.

Channel Assignment via Graphs The diameter of the graph G, diam(G), is the longest distance in the graph. Model: vertices correspond to transmitters. The distance between vertices u and v, d(u,v), is the length of the shortest path between u and v. u v w d(u,v) = 3 d(w,v) = 4 diam(G) = 4

Defining Distance Labeling All graph labeling starts with a function f : V(G) → N that satisfies some conditions. f(v) = 3 f(w) = w v

Some distance labeling schemes f : V(G) → N satisfies ______________ k-labeling: Antipodal:(same) Radio: (same) L d (2,1):

Radio: The radio number of a graph G, rn(G), is the smallest integer m such that G has a radio labeling f with m = max{f(v) | v in V(G)}. rn(P 4 ) = 6

Radio Numbers of Graph Families Standard problem: find rn(G) for all graphs G belonging to some family of graphs. “… determining the radio number seems a difficult problem even for some basic families of graphs.” (Liu and Zhu)  Complete graphs, wheels, stars (generally known) S54S diam(S n ) = 2 rn(S n ) = n + 1

Radio Numbers of Graph Families  Complete k-partite graphs (Chartrand, Erwin, Harary, Zhang)  Paths and cycles (Liu, Zhu)  Squares of paths and cycles (Liu, Xie)  Spiders (Liu)

Radio Numbers of Graph Families  Gears (REU ’06)  Products of cycles (REU ’06)  Generalized prisms (REU ’06)  Grids* (REU ’08)  Ladders (REU ’08)  Generalized gears* (REU ’09)  Generalized wheels* (REU ’09)  Unnamed families (REU ’09)

Radio Numbers & Graph Properties  Diameter  Girth  Connectivity  (your favorite set of graph properties) Question: What can be said about the radio numbers of graphs with these properties?

E.g. products of graphs The (box) product of graphs G and H, G □ H, is the graph with vertex set V(G) × V(H), where (g 1, h 1 ) is adjacent to (g 2, h 2 ) if and only if g 1 = g 2 and h 1 is adjacent to h 2 (in H), and h 1 = h 2 and g 1 is adjacent to g 2 (in G). a b (a, 1) (b, 3) (a, 5) (b, 5) Radio Numbers & Graph Operations

Graph Numbers and Box Products  Coloring: χ(G□H) = max{χ(G), χ(H)}  Graham’s Conjecture: π(G□H) ≤ π(G) ∙ π(H)  Optimal pebbling: g(G□H) ≤ g(G) ∙ g(H) Question: Can rn(G □ H) be determined by rn(G) and rn(H)? If not, what else is needed?

REU ’07 students at JMM Bounds on radio numbers of products of graphs

REU ‘07 Results – Lower Bounds Radio Numbers: rn(G □ H) ≥ rn(G) ∙ rn(H) - 2 Number of Vertices: rn(G □ H) ≥ |V(G)| ∙ |V(H)| Gaps: rn(G □ H) ≥ (½(|V(G)|∙|V(H)| - 1)(φ(G) - φ(H) – 2)

Analysis of Lower Bounds Product Radio No. VerticesGap C 4 □ P 2 58– C n □ P 2 C n □ P 2 n 2 /8 2n2n2n2n– C 4 □ C C n □ C n n 2 /4 n 3 /8 n2n2n2n2 P 4 □ P P 100 □ P 100 9,80010,000499,902 P n □ P n n2n2n2n2 n2n2n2n2 n 3 /4 Pete □ Pete

Theorem (REU ’07): Assume G and H are graphs satisfying diam(G) - diam(H) ≥ 2 as well as rn(G) = n and rn(H) = m. Then rn(G □ H) ≤ diam(G)(n+m-2) + 2mn - 4n - 2m + 8. REU ’07 proved two other theorems providing upper bounds under different hypotheses. REU ‘07 Results – Upper Bounds

Need lemma giving M = max{d(u,v)+d(v,w)+d(w,v)}. Assume f(u) < f(v) < f(w). Summing the radio condition d(u,v) + |f(u) - f(v)| ≥ diam(G) + 1 for each pair of vertices in {u, v, w} gives M + 2f(w) – 2f(u) ≥ 3 diam(G) + 3 i.e. f(w) – f(u) ≥ ½(3 diam(G) + 3 – M). Using Gaps

Have f(w) – f(u) ≥ ½(3 diam(G) + 3 – M) = gap. If |V(G)| = n, this yields Using Gaps, cont. gap + 1 gap + 2 gap 2gap + 2 2gap + 1 gap 12

Using Gaps to Determine a Lower Bound for the Radio Number of Prisms Y6Y6 Choose any three vertices u, v, and w. d(u,v) + d(u,w) + d(v,w) ≤ 2∙diam(Y n ) (n even) u v w

Assume we have a radio labeling f of Y n, and f(u) < f(v) < f(w). Then

Strategies for establishing an upper bound for rn(G) Define a labeling, prove it’s a radio labeling, determine the maximum label. Might use an intermediate labeling that orders the vertices {x 1, x 2, … x s } so that f(x i ) > f(x j ) iff i > j. Using patterns, iteration, symmetry, etc. to define a labeling makes it easier to prove it’s a radio labeling.