Tree Spanners for Bipartite Graphs and Probe Interval Graphs Andreas Brandstädt 1, Feodor Dragan 2, Oanh Le 1, Van Bang Le 1, and Ryuhei Uehara 3 1 Universität.

Slides:



Advertisements
Similar presentations
Bart Jansen 1.  Problem definition  Instance: Connected graph G, positive integer k  Question: Is there a spanning tree for G with at least k leaves?
Advertisements

Distance and Routing Labeling Schemes in Graphs
Compact and Low Delay Routing Labeling Scheme for Unit Disk Graphs Chenyu Yan, Yang Xiang, and Feodor F. Dragan (WADS 2009) Kent State University, Kent,
Bart Jansen, Utrecht University. 2  Max Leaf  Instance: Connected graph G, positive integer k  Question: Is there a spanning tree for G with at least.
Bart Jansen, Utrecht University. 2  Max Leaf  Instance: Connected graph G, positive integer k  Question: Is there a spanning tree for G with at least.
Fractional Cascading CSE What is Fractional Cascading anyway? An efficient strategy for dealing with iterative searches that achieves optimal.
On the complexity of orthogonal compaction maurizio patrignani univ. rome III.
Graph Classes A Survey 張貿翔 中正大學資訊工程學系. Meeting Room Reservation One meeting room Reservation: –Gary10:00~11:00 –Mary10:30~12:00 –Jones13:30~14:30 –Amy14:00~15:30.
WG’2001 June 14 Boltenhagen near Rostock, Germany 1 Estimating All Pairs Shortest Paths in Restricted Graph Families: A Unified Approach Feodor F. Dragan.
Toshiki Saitoh ERATO, Minato Project, JST Subgraph Isomorphism in Graph Classes Joint work with Yota Otachi, Shuji Kijima, and Takeaki Uno The 14 th Korea-Japan.
Reconstruction Algorithm for Permutation Graphs Masashi Kiyomi, Toshiki Saitoh, and Ryuhei Uehara School of Information Science Japan Advanced Institute.
CSC5160 Topics in Algorithms Tutorial 2 Introduction to NP-Complete Problems Feb Jerry Le
1 Discrete Structures & Algorithms Graphs and Trees: II EECE 320.
1 Representing Graphs. 2 Adjacency Matrix Suppose we have a graph G with n nodes. The adjacency matrix is the n x n matrix A=[a ij ] with: a ij = 1 if.
Decomposition of overlapping protein complexes: A graph theoretical method for analyzing static and dynamic protein associations Algorithms for Molecular.
Data Transmission and Base Station Placement for Optimizing Network Lifetime. E. Arkin, V. Polishchuk, A. Efrat, S. Ramasubramanian,V. PolishchukA. EfratS.
1 University of Freiburg Computer Networks and Telematics Prof. Christian Schindelhauer Wireless Sensor Networks 21st Lecture Christian Schindelhauer.
Vertex Cover, Dominating set, Clique, Independent set
Network Flow Spanners F. F. Dragan and Chenyu Yan Kent State University, Kent, OH, USA.
Generalized Powers of Graphs and their Algorithmic Use A. Brandstädt, F.F. Dragan, Y. Xiang, and C. Yan University of Rostock, Germany Kent State University,
Collective Additive Tree Spanners of Homogeneously Orderable Graphs
Collective Tree Spanners of Graphs with Bounded Parameters F.F. Dragan and C. Yan Kent State University, USA.
CS541 Advanced Networking 1 Routing and Shortest Path Algorithms Neil Tang 2/18/2009.
Collective Tree Spanners of Graphs F.F. Dragan, C. Yan, I. Lomonosov Kent State University, USA Hiram College, USA.
Collective Tree Spanners and Routing in AT-free Related Graphs F.F. Dragan, C. Yan, D. Corneil Kent State University University of Toronto.
Coloring Algorithms and Networks. Coloring2 Graph coloring Vertex coloring: –Function f: V  C, such that for all {v,w}  E: f(v)  f(w) Chromatic number.
Additive Spanners for k-Chordal Graphs V. D. Chepoi, F.F. Dragan, C. Yan University Aix-Marseille II, France Kent State University, Ohio, USA.
Steiner trees Algorithms and Networks. Steiner Trees2 Today Steiner trees: what and why? NP-completeness Approximation algorithms Preprocessing.
Finding a maximum independent set in a sparse random graph Uriel Feige and Eran Ofek.
CPSC 689: Discrete Algorithms for Mobile and Wireless Systems Spring 2009 Prof. Jennifer Welch.
Complexity results for three-dimensional orthogonal graph drawing maurizio “titto” patrignani third university of rome graph drawing 2005.
The complexity of the matching-cut problem Maurizio Patrignani & Maurizio Pizzonia Third University of Rome.
Distance Approximating Trees in Graphs
LATIN’02 April 4 Cancun, Mexico 1 On the Power of BFS to Determine a Graph’s Diameter Derek G. Corneil University of Toronto Feodor F. Dragan Kent State.
All that remains is to connect the edges in the variable-setters to the appropriate clause-checkers in the way that we require. This is done by the convey.
1 Graph Searching and Search Time Franz J. Brandenburg and Stefanie Herrmann University of Passau.
Toshiki Saitoh ERATO, Minato Discrete Structure Manipulation System Project, JST Graph Classes and Subgraph Isomorphism Joint work with Yota Otachi, Shuji.
Graphs represented by words Sergey Kitaev Reykjavik University Sobolev Institute of Mathematics Joint work with Artem Pyatkin Magnus M. Halldorsson Reykjavik.
1 Treewidth, partial k-tree and chordal graphs Delpensum INF 334 Institutt fo informatikk Pinar Heggernes Speaker:
Stephane Durocher 1 Debajyoti Mondal 1 Md. Saidur Rahman 2 1 Department of Computer Science, University of Manitoba 2 Department of Computer Science &
Constructing evolutionary trees from rooted triples Bang Ye Wu Dept. of Computer Science and Information Engineering Shu-Te University.
The Lower Bounds of Problems
Incidentor coloring: methods and results A.V. Pyatkin "Graph Theory and Interactions" Durham, 2013.
On Leaf Powers Andreas Brandstädt University of Rostock, Germany (joint work with Van Bang Le, Peter Wagner, Christian Hundt, and R. Sritharan)
Memory Allocation of Multi programming using Permutation Graph By Bhavani Duggineni.
CSE 421 Algorithms Richard Anderson Lecture 27 NP-Completeness and course wrap up.
The Dominating Set and its Parametric Dual  the Dominated Set  Lan Lin prepared for theory group meeting on June 11, 2003.
Lecture 6 NP Class. P = ? NP = ? PSPACE They are central problems in computational complexity.
Tree Spanners on Chordal Graphs: Complexity, Algorithms, Open Problems A. Brandstaedt, F.F. Dragan, H.-O. Le and V.B. Le University of Rostock, Germany.
1 IM.CJCU Hsin-Hung Chou The Node-Searching Problem on Special Graphs 周信宏 長榮大學 資訊管理學系
Strings Basic data type in computational biology A string is an ordered succession of characters or symbols from a finite set called an alphabet Sequence.
Data Reduction for Graph Coloring Problems Bart M. P. Jansen Joint work with Stefan Kratsch August 22 nd 2011, Oslo.
Lecture 25 NP Class. P = ? NP = ? PSPACE They are central problems in computational complexity.
A randomized linear time algorithm for graph spanners Surender Baswana Postdoctoral Researcher Max Planck Institute for Computer Science Saarbruecken,
NPC.
Graphs Definition: a graph is an abstract representation of a set of objects where some pairs of the objects are connected by links. The interconnected.
Spanning Tree Definition:A tree T is a spanning tree of a graph G if T is a subgraph of G that contains all of the vertices of G. A graph may have more.
A linear-time algorithm to compute a MAD tree of an interval graph Elias Dahlhaus, Peter Dankelmann, R.Ravi.
Kernel Bounds for Path and Cycle Problems Bart M. P. Jansen Joint work with Hans L. Bodlaender & Stefan Kratsch September 8 th 2011, Saarbrucken.
2005/3/1 Efficient Algorithms for the Longest Path Problem Ryuhei UEHARA (JAIST) Yushi UNO (Osaka.
1 Variations of the maximum leaf spanning tree problem for bipartite graphs P.C. Li and M. Toulouse Information Processing Letters 97 (2006) /03/14.
On Variants of Induced Matchings Andreas Brandstädt University of Rostock, Germany (joint work with Raffaele Mosca and Ragnar Nevries)
Quiz Review.
Distance and Routing Labeling Schemes in Graphs
Distance Approximating Trees in Graphs Brandstaedt & Chepoi & Dragan, ESA’97, J. of Algorithms ’99, European J. of Combinatorics 2000 A graph G=(V,E)
Trees.
Md. Abul Kashem, Chowdhury Sharif Hasan, and Anupam Bhattacharjee
Feodor F. Dragan 1990 Ph.D. in Theoretical Computer Science Institute of Mathematics of the Byelorussian Academy of Science, Minsk Moldova State University.
Distance Approximating Trees: Complexity and Algorithms
How to use spanning trees to navigate in Graphs
Presentation transcript:

Tree Spanners for Bipartite Graphs and Probe Interval Graphs Andreas Brandstädt 1, Feodor Dragan 2, Oanh Le 1, Van Bang Le 1, and Ryuhei Uehara 3 1 Universität Rostock 2 Kent State University 3 Komazawa University

Tree Spanners for Bipartite Graphs and Probe Interval Graphs Andreas Brandstädt 1, Feodor Dragan 2, Oanh Le 1, Van Bang Le 1, and Ryuhei Uehara 3 1 Universität Rostock 2 Kent State University 3 Komazawa University

Tree Spanner Spanning tree T is a tree t-spanner iff d T (x,y) ≦ t d G (x,y) for all x and y in V. G T x y x y

Tree Spanner Spanning tree T is a tree t-spanner iff G T d T (x,y) ≦ t d G (x,y) for all {x,y} in E.

Tree Spanner Spanning tree T is a tree 6-spanner. G T

Tree Spanner G admits a tree 4-spanner (which is optimal). Tree t-spanner problem asks if G admits a tree t-spanner for given t. G T

Applications in distributed systems and communication networks synchronizers in parallel systems topology for message routing there is a very good algorithm for routing in trees in biology evolutionary tree reconstruction in approximation algorithms approximating the bandwidth of graphs Any problem related to distances can be solved approximately on a complex graph if it admits a good tree spanner G 7-spanner for G

Known Results for tree t -spanner general graphs [Cai&Corneil’95] a linear time algorithm for t =2 (t=1 is trivial) tree t -spanner is NP-complete for any t ≧ 4 ( ⇒ NP-completeness of bipartite graphs for t ≧ 5) tree t -spanner is Open for t=3

Known Results for tree t -spanner chordal graphs [Brandst ä dt, Dragan, Le & Le ’02] tree t -spanner is NP-complete for any t ≧ 4 tree 3-spanner admissible graphs [a Number of Authors] cographs, complements of bipartite graphs, interval graphs, directed path graphs, split graphs, permutation graphs, convex bipartite graphs, regular bipartite graphs, distance-hereditary graphs tree 4-spanner admissible graphs AT-free graphs [PKLMW’99], strongly chordal graphs, dually chordal graphs [BCD’99] tree 3 -spanner is in P for planar graphs [FK’2001]

Known Results for tree t -spanner chordal graphs [Brandst ä dt, Dragan, Le & Le ’02] tree t -spanner is NP-complete for any t ≧ 4 tree 3-spanner admissible graphs [a Number of Authors] cographs, complements of bipartite graphs, interval graphs, directed path graphs, split graphs, permutation graphs, convex bipartite graphs, regular bipartite graphs, distance-hereditary graphs tree 4-spanner admissible graphs AT-free graphs [PKLMW’99], strongly chordal graphs, dually chordal graphs [BCD’99] tree 3 -spanner is in P for planar graphs [FK’2001] ⇒ Bipartite Graphs??

Known Results for tree t -spanner bipartite graphs [Cai&Corneil ’95] tree t -spanner is NP-complete for any t ≧ 5 chordal graphs [Brandst ä dt, Dragan, Le & Le ’02] tree t -spanner is NP-complete for any t ≧ 4 tree 3-spanner admissible graphs [a Number of Authors] cographs, complements of bipartite graphs, interval graphs, directed path graphs, split graphs, permutation graphs, convex bipartite graphs, regular bipartite graphs, distance-hereditary graphs convex bipartite ⊂ interval bigraphs ⊂ bipartite ATE-free graphs ⊂ chordal bipartite graphs ⊂ bipartite graphs

This Talk interval rooted directed path strongly chordal weakly chordal bipartite interval bigraph convex AT-free bipartite ATE-free bipartite NP-C 4-Adm. 3-Adm.

This Talk interval rooted directed path strongly chordal weakly chordal enhanced probe interval chordal bipartite probe interval bigraph convex STS-probe interval AT-free bipartite ATE-free bipartite NP-C 4-Adm. 3-Adm. =

This Talk interval rooted directed path strongly chordal weakly chordal enhanced probe interval chordal bipartite probe interval bigraph convex STS-probe interval AT-free bipartite ATE-free bipartite NP-C 4-Adm. 3-Adm. = 7-Adm.

NP-hardness for chordal bipartite graphs [Thm] For any t ≧ 5, the tree t-spanner problem is NP-complete for chordal bipartite graphs. Reduction from 3SAT Monotone … (x, y, z) or (x, y, z)

NP-hardness for chordal bipartite graphs Reduction from 3SAT Basic gadgets Monotone … (x, y, z) or (x, y,z) S 1 [a,b]S 2 [a,b]S 3 [a,b] a a’ b b’ ab a’b’ S 1 [a,a’] S 1 [a’,b’] S 1 [b,b’] S 2 [a,a’] S 2 [a’,b’] S 2 [b,b’] ab a’b’

NP-hardness for chordal bipartite graphs Reduction from 3SAT Basic gadget S k [a,b] and its spanning trees Monotone … (x, y, z) or (x, y,z) a a’ b b’ a a’ b b’ a a’ b b’ H with {a,b} (2k+1)-spanner without {a,b} h (2k+h)-spanner a a’ b b’ without {a,b} (2k-1)-spanner

NP-hardness for chordal bipartite graphs Reduction from 3SAT Gadget for x i Monotone … (x, y, z) or (x, y,z) qr sp xixi xixi xixi xixi xixi xixi 1 2 m 1 2 m … … S k-1 [] S k []× 2 = = Must be selected

NP-hardness for chordal bipartite graphs Reduction from 3SAT Gadget for C j Monotone … (x, y, z) or (x, y,z) cjcj cjcj djdj djdj S k []× 2=

NP-hardness for chordal bipartite graphs Reduction from 3SAT Gadget for C 1 =(x 1,x 2,x 3 ) and C 2 =(x 1,x 2,x 4 ) Monotone … (x, y, z) or (x, y,z) qr sp x1x1 x1x1 x1x1 x1x S k-2 [] = x2x2 x2x2 x2x2 x2x x3x3 x3x3 x3x3 x3x x4x4 x4x4 x4x4 x4x c1c1 c1c1 d1d1 d1d c2c2 c2c2 d2d2 d2d

Tree 3-spanner for a bipartite ATE-free graph An ATE(Asteroidal-Triple-Edge) e 1,e 2,e 3 [Mul97]: Any two of them there is a path from one to the other avoids the neighborhood of the third one. [Lamma] interval bigraphs ⊂ bipartite ATE-free graphs ⊂ chordal bipartite graphs. e1e1 e3e3 e2e2

Tree 3-spanner for a bipartite ATE-free graph A maximum neighbor w of u: N(N(u))=N(w) [Lamma] Any chordal bipartite graph has a vertex with a maximum neighbor. u w chordal bipartite graph ⇔ bipartite graph any cycle of length at least 6 has a chord

Tree 3-spanner for a bipartite ATE-free graph G; connected bipartite ATE-free graph u; a vertex with maximum neighbor For any connected component S induced by V \ D k-1 (u), there is w in N k-1 (u) s.t. N(w) ⊇ S∩N k (u) S u … w

Tree 3-spanner for a bipartite ATE-free graph Construction of a tree 3-spanner of G: u; a vertex with maximum neighbor u … w

Conclusion and open problems Many questions remain still open. Among them: Can Tree 3–Spanner be decided efficiently on general graphs??? on chordal graphs? on chordal bipartite graphs? Tree t – Spanner on (enhanced) probe interval graphs for t<7? Thank you!