Treffer: On the parallel computation of the biconnected and strongly connected co-components of graphs

Title:
On the parallel computation of the biconnected and strongly connected co-components of graphs
Source:
3rd Cologne/Twente Workshop on Graphs and Combinatorial OptimizationDiscrete applied mathematics. 155(14):1858-1877
Publisher Information:
Amsterdam; Lausanne; New York, NY: Elsevier, 2007.
Publication Year:
2007
Physical Description:
print, 24 ref
Original Material:
INIST-CNRS
Subject Terms:
Control theory, operational research, Automatique, recherche opérationnelle, Computer science, Informatique, Mathematics, Mathématiques, Sciences exactes et technologie, Exact sciences and technology, Sciences et techniques communes, Sciences and techniques of general use, Mathematiques, Mathematics, Combinatoire. Structures ordonnées, Combinatorics. Ordered structures, Combinatoire, Combinatorics, Sciences appliquees, Applied sciences, Informatique; automatique theorique; systemes, Computer science; control theory; systems, Informatique théorique, Theoretical computing, Algorithmique. Calculabilité. Arithmétique ordinateur, Algorithmics. Computability. Computer arithmetics, Recherche information. Graphe, Information retrieval. Graph, Logiciel, Software, Organisation des mémoires. Traitement des données, Memory organisation. Data processing, Traitement des données. Listes et chaînes de caractères, Data processing. List processing. Character string processing, Algorithme optimal, Optimal algorithm, Algoritmo óptimo, Algorithme parallèle, Parallel algorithm, Algoritmo paralelo, Calcul automatique, Computing, Cálculo automático, Calcul parallèle, Parallel computation, Cálculo paralelo, Combinatoire, Combinatorics, Combinatoria, Complexité temps, Time complexity, Complejidad tiempo, Connectivité graphe, Graph connectivity, Conectividad grafo, Entrée ordinateur, Input, Entrada ordenador, Informatique théorique, Computer theory, Informática teórica, Optimisation, Optimization, Optimización, Parallélisation, Parallelization, Paralelisacíon, Processeur, Processor, Procesador, Recherche profondeur d'abord, First depth search, Busca profundidad primero, Structure donnée, Data structure, Estructura datos, 68P05, 68Q10, 68R10, 68W10, 68Wxx, Algorithme séquentiel, Composante biconnexe, Composante connexe, Graphe fortement connexe, Recherche largeur d'abord, Biconnected and co-biconnected components, Co-biconnectivity algorithms, Parallel algorithms, Strong co-connectivity algorithms, Strongly connected and co-connected components
Document Type:
Konferenz Conference Paper
File Description:
text
Language:
English
Author Affiliations:
Department of Computer Science, University of Ioannina, P.O. Box 1186, 45110 Ioannina, Greece
ISSN:
0166-218X
Rights:
Copyright 2008 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

Mathematics
Accession Number:
edscal.19046568
Database:
PASCAL Archive

Weitere Informationen

In this paper, we consider the problems of co-biconnectivity and strong co-connectivity, i.e., computing the biconnected components and the strongly connected components of the complement of a given graph. We describe simple sequential algorithms for these problems, which work on the input graph and not on its complement, and which for a graph on n vertices and m edges both run in optimal O(n + m) time. Our algorithms are not data structure-based and they employ neither breadth-first-search nor depth-first-search. Unlike previous linear co-biconnectivity and strong co-connectivity sequential algorithms, both algorithms admit efficient parallelization. The co-biconnectivity algorithm can be parallelized resulting in an optimal parallel algorithm that runs in O(log2 n) time using O((n + m)/log2 n) processors. The strong co-connectivity algorithm can also be parallelized to yield an O(log2 n)-time and O(m1.88/ log n)-processor solution. As a byproduct, we obtain a simple optimal O(log n)-time parallel co-connectivity algorithm. Our results show that, in a parallel process environment, the problems of computing the biconnected components and the strongly connected components can be solved with better time-processor complexity on the complement of a graph rather than on the graph itself.