Result: Parameterized counting algorithms for general graph covering problems

Title:
Parameterized counting algorithms for general graph covering problems
Source:
Algorithms and data structurese (Waterloo ON, 15-17 August 2005)Lecture notes in computer science. :99-109
Publisher Information:
Berlin: Springer, 2005.
Publication Year:
2005
Physical Description:
print, 6 ref
Original Material:
INIST-CNRS
Document Type:
Conference Conference Paper
File Description:
text
Language:
English
Author Affiliations:
School of Computer Science, University of Waterloo, Waterloo, Ontario, N2L 3G1, Canada
Departament de Llenguatges i Sistemes Informàtics, Universitat Politècnica de Catalunya, Campus Nord, Desp. Q-228, c/Jordi Girona Salgado, 1-3, 08034, Barcelona, Spain
ISSN:
0302-9743
Rights:
Copyright 2005 INIST-CNRS
CC BY 4.0
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
Notes:
Computer science; theoretical automation; systems
Accession Number:
edscal.17116305
Database:
PASCAL Archive

Further Information

We examine the general problem of covering graphs by graphs: given a graph G, a collection P of graphs each on at most p vertices, and an integer r, is there a collection C of subgraphs of G, each belonging to P, such that the removal of the graphs in C from G creates a graph none of whose components have more than r vertices? We can also require that the graphs in C be disjoint (forming a matching). This framework generalizes vertex cover, edge dominating set, and minimal maximum matching. In this paper, we examine the parameterized complexity of the counting version of the above general problem. In particular, we show how to count the solutions of size at most k of the covering and matching problems in time O(n.r(pk+r)+2f(k,p,r)), where n is the number of vertices in G and f is a simple polynomial. In order to achieve the additive relation between the polynomial and the non-polynomial parts of the time complexity of our algorithms, we use the compactor technique, the counting analogue of kernelization for parameterized decision problems.