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37
A review of routing and wavelength assignment approaches for wavelengthrouted optical WDM networks
 Optical Networks Magazine
, 2000
"... This study focuses on the routing and WavelengthAssignment (RWA) problem in wavelengthrouted optical WDM networks. Most of the attention is devoted to such networks operating under the wavelengthcontinuity constraint, in which lightpaths are set up for connection requests between node pairs, and ..."
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Cited by 307 (11 self)
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This study focuses on the routing and WavelengthAssignment (RWA) problem in wavelengthrouted optical WDM networks. Most of the attention is devoted to such networks operating under the wavelengthcontinuity constraint, in which lightpaths are set up for connection requests between node pairs, and a single lightpath must occupy the same wavelength on all of the links that it spans. In setting up a lightpath, a route must be selected and a wavelength must be assigned to the lightpath. If no wavelength is available for this lightpath on the selected route, then the connection request is blocked. We examine the RWA problem and review various routing approaches and wavelengthassignment approaches proposed in the literature. We also briefly consider the characteristics of wavelengthconverted networks (which do not have the wavelengthcontinuity constraint), and we examine the associated research problems and challenges. Finally, we propose a new wavelengthassignment scheme, called Distributed Relative Capacity Loss (DRCL), which works well in distributedcontrolled networks, and we demonstrate the performance of DRCL through simulation. 1
A Clustering Algorithm based on Graph Connectivity
 Information Processing Letters
, 1999
"... We have developed a novel algorithm for cluster analysis that is based on graph theoretic techniques. ..."
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Cited by 136 (3 self)
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We have developed a novel algorithm for cluster analysis that is based on graph theoretic techniques.
An Algorithm for Clustering cDNAs for Gene Expression Analysis
 In RECOMB99: Proceedings of the Third Annual International Conference on Computational Molecular Biology
, 1999
"... We have developed a novel algorithm for cluster analysis that is based on graph theoretic techniques. A similarity graph is defined and clusters in that graph correspond to highly connected subgraphs. A polynomial algorithm to compute them efficiently is presented. Our algorithm produces a clusterin ..."
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Cited by 52 (4 self)
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We have developed a novel algorithm for cluster analysis that is based on graph theoretic techniques. A similarity graph is defined and clusters in that graph correspond to highly connected subgraphs. A polynomial algorithm to compute them efficiently is presented. Our algorithm produces a clustering with some provably good properties. The application that motivated this study was gene expression analysis, where a collection of cDNAs must be clustered based on their oligonucleotide fingerprints. The algorithm has been tested intensively on simulated libraries and was shown to outperform extant methods. It demonstrated robustness to high noise levels. In a blind test on real cDNA fingerprint data the algorithm obtained very good results. Utilizing the results of the algorithm would have saved over 70% of the cDNA sequencing cost on that data set. 1 Introduction Cluster analysis seeks grouping of data elements into subsets, so that elements in the same subset are in some sense more cl...
Community landscapes: an integrative approach to determine overlapping network module hierarchy, identify key nodes and predict network dynamics
 PLoS One
, 2010
"... Background: Network communities help the functional organization and evolution of complex networks. However, the development of a method, which is both fast and accurate, provides modular overlaps and partitions of a heterogeneous network, has proven to be rather difficult. Methodology/Principal Fin ..."
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Cited by 17 (1 self)
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Background: Network communities help the functional organization and evolution of complex networks. However, the development of a method, which is both fast and accurate, provides modular overlaps and partitions of a heterogeneous network, has proven to be rather difficult. Methodology/Principal Findings: Here we introduce the novel concept of ModuLand, an integrative method family determining overlapping network modules as hills of an influence functionbased, centralitytype community landscape, and including several widely used modularization methods as special cases. As various adaptations of the method family, we developed several algorithms, which provide an efficient analysis of weighted and directed networks, and (1) determine pervasively overlapping modules with high resolution; (2) uncover a detailed hierarchical network structure allowing an efficient, zoomin analysis of large networks; (3) allow the determination of key network nodes and (4) help to predict network dynamics. Conclusions/Significance: The concept opens a wide range of possibilities to develop new approaches and applications
Quantitative methods for studying social context in multilevels and through interpersonal relations
 Review of Research in Education
, 1998
"... The online version of this article can be found at: Published on behalf of ..."
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Cited by 10 (1 self)
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The online version of this article can be found at: Published on behalf of
Communities in Graphs
 of Lecture Notes in Computer Science
, 2002
"... Many applications, like the retrieval of information from the WWW, require or are improved by the detection of sets of closely related vertices in graphs. Depending on the application, many approaches are possible. In this paper we present a purely graphtheoretical approach, independent of the repr ..."
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Cited by 8 (1 self)
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Many applications, like the retrieval of information from the WWW, require or are improved by the detection of sets of closely related vertices in graphs. Depending on the application, many approaches are possible. In this paper we present a purely graphtheoretical approach, independent of the represented data. Based on the edgeconnectivity of subgraphs, a tree of subgraphs is constructed, such that the children of a node are pairwise disjoint and contained in their parent. We describe a polynomial algorithm for the construction of the tree and present two heuristics, constructing the correct result in signi cantly decreased time. Furthermore we give a short description of possible applications in the elds of information retrieval, clustering and graph drawing. 1.
Accelerating Screening of 3D Protein Data with a Graph Theoretical Approach
, 2003
"... Motivation. The Dictionary of Interfaces in Proteins (DIP) is a data base collecting the threedimensional structure of interacting parts of proteins that are called patches. It serves as a repository, in which patches similar to given query patches can be found. The computation of the similarit ..."
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Cited by 7 (4 self)
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Motivation. The Dictionary of Interfaces in Proteins (DIP) is a data base collecting the threedimensional structure of interacting parts of proteins that are called patches. It serves as a repository, in which patches similar to given query patches can be found. The computation of the similarity of two patches is time consuming and traversing the entire DIP requires some hours. In this work we address the question how the patches similar to a given query, can be identified by scanning only a small part of DIP. The answer to this question requires the investigation of the distribution of the similarity of patches. Results. The score
A topologydriven approach to the design of web metasearch clustering engines
, 2003
"... The paradigm adopted by classical Web search engines to output the results of a query is often inadequate. It typically consists of a ranked list of URLs, which may be very long and difficult to browse for the interested user. Recently, a lot of attention has been devoted to the design of Web metas ..."
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Cited by 5 (1 self)
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The paradigm adopted by classical Web search engines to output the results of a query is often inadequate. It typically consists of a ranked list of URLs, which may be very long and difficult to browse for the interested user. Recently, a lot of attention has been devoted to the design of Web metasearch clustering engines. These systems support the user by grouping the URLs returned by a search engine into distinct semantic categories, which are organized in a hierarchy; each category is properly labeled with a sentence that reflects its topics. However, even the most effective Web metasearch engines usually endup by presenting many “meaningful ” categories together with a few “inexpressive ” categories on some specific queries. In this paper we describe a novel topologydriven approach to the design of a Web metasearch clustering engine. By this approach the set of URLs is modeled as a suitable graph and the hierarchy of categories is obtained by variants of classical graphclustering algorithms. The topologydriven approach turns out to be comparable with traditional textbased strategies for the definition of the cluster hierarchy. In addition, our approach makes it natural to use graph visualization techniques to support the user in handling inexpressive labels. Namely, categories with inexpressive labels can be visually related to more meaningful ones.