90 research outputs found
Hierarchies of Predominantly Connected Communities
We consider communities whose vertices are predominantly connected, i.e., the
vertices in each community are stronger connected to other community members of
the same community than to vertices outside the community. Flake et al.
introduced a hierarchical clustering algorithm that finds such predominantly
connected communities of different coarseness depending on an input parameter.
We present a simple and efficient method for constructing a clustering
hierarchy according to Flake et al. that supersedes the necessity of choosing
feasible parameter values and guarantees the completeness of the resulting
hierarchy, i.e., the hierarchy contains all clusterings that can be constructed
by the original algorithm for any parameter value. However, predominantly
connected communities are not organized in a single hierarchy. Thus, we develop
a framework that, after precomputing at most maximum flows, admits a
linear time construction of a clustering \C(S) of predominantly connected
communities that contains a given community and is maximum in the sense
that any further clustering of predominantly connected communities that also
contains is hierarchically nested in \C(S). We further generalize this
construction yielding a clustering with similar properties for given
communities in time. This admits the analysis of a network's structure
with respect to various communities in different hierarchies.Comment: to appear (WADS 2013
All-Pairs Minimum Cuts in Near-Linear Time for Surface-Embedded Graphs
For an undirected -vertex graph with non-negative edge-weights, we
consider the following type of query: given two vertices and in ,
what is the weight of a minimum -cut in ? We solve this problem in
preprocessing time for graphs of bounded genus, giving the first
sub-quadratic time algorithm for this class of graphs. Our result also improves
by a logarithmic factor a previous algorithm by Borradaile, Sankowski and
Wulff-Nilsen (FOCS 2010) that applied only to planar graphs. Our algorithm
constructs a Gomory-Hu tree for the given graph, providing a data structure
with space that can answer minimum-cut queries in constant time. The
dependence on the genus of the input graph in our preprocessing time is
Algorithms for Graph Connectivity and Cut Problems - Connectivity Augmentation, All-Pairs Minimum Cut, and Cut-Based Clustering
We address a collection of related connectivity and cut problems in simple graphs that reach from the augmentation of planar graphs to be k-regular and c-connected to new data structures representing minimum separating cuts and algorithms that smoothly maintain Gomory-Hu trees in evolving graphs, and finally to an analysis of the cut-based clustering approach of Flake et al. and its adaption to dynamic scenarios
Optimization in Telecommunication Networks
Network design and network synthesis have been the classical optimization problems intelecommunication for a long time. In the recent past, there have been many technologicaldevelopments such as digitization of information, optical networks, internet, and wirelessnetworks. These developments have led to a series of new optimization problems. Thismanuscript gives an overview of the developments in solving both classical and moderntelecom optimization problems.We start with a short historical overview of the technological developments. Then,the classical (still actual) network design and synthesis problems are described with anemphasis on the latest developments on modelling and solving them. Classical results suchas Menger’s disjoint paths theorem, and Ford-Fulkerson’s max-flow-min-cut theorem, butalso Gomory-Hu trees and the Okamura-Seymour cut-condition, will be related to themodels described. Finally, we describe recent optimization problems such as routing andwavelength assignment, and grooming in optical networks.operations research and management science;
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