333 research outputs found
Partitioning Complex Networks via Size-constrained Clustering
The most commonly used method to tackle the graph partitioning problem in
practice is the multilevel approach. During a coarsening phase, a multilevel
graph partitioning algorithm reduces the graph size by iteratively contracting
nodes and edges until the graph is small enough to be partitioned by some other
algorithm. A partition of the input graph is then constructed by successively
transferring the solution to the next finer graph and applying a local search
algorithm to improve the current solution.
In this paper, we describe a novel approach to partition graphs effectively
especially if the networks have a highly irregular structure. More precisely,
our algorithm provides graph coarsening by iteratively contracting
size-constrained clusterings that are computed using a label propagation
algorithm. The same algorithm that provides the size-constrained clusterings
can also be used during uncoarsening as a fast and simple local search
algorithm.
Depending on the algorithm's configuration, we are able to compute partitions
of very high quality outperforming all competitors, or partitions that are
comparable to the best competitor in terms of quality, hMetis, while being
nearly an order of magnitude faster on average. The fastest configuration
partitions the largest graph available to us with 3.3 billion edges using a
single machine in about ten minutes while cutting less than half of the edges
than the fastest competitor, kMetis
A trilogy of tragedies - paediatric dental tooth whitening
Dental tooth whitening is used throughout the United Kingdom for patients who have aesthetic concerns regarding the colour of their teeth. Up until recent months it was also frequently used for paediatric patients with enamel opacities of cosmetic concern and discoloured non-vital anterior teeth. This safe and effective treatment option is now not available to paediatric dental patients due to changes in indemnity cover, and we demonstrate three cases from our department where dental whitening was the most appropriate treatment option. By removing this treatment option for selected paediatric patients, we are concerned that more destructive and less effective treatments may be performed with short- and long-term detriment to their oral health. Furthermore, failure to provide any treatment may negatively affect children's quality of life and psychological well-being
186 Transient elastography can be used to guide monitoring of cystic fibrosis related liver disease in adult patients
A Distributed Multilevel Force-directed Algorithm
The wide availability of powerful and inexpensive cloud computing services
naturally motivates the study of distributed graph layout algorithms, able to
scale to very large graphs. Nowadays, to process Big Data, companies are
increasingly relying on PaaS infrastructures rather than buying and maintaining
complex and expensive hardware. So far, only a few examples of basic
force-directed algorithms that work in a distributed environment have been
described. Instead, the design of a distributed multilevel force-directed
algorithm is a much more challenging task, not yet addressed. We present the
first multilevel force-directed algorithm based on a distributed vertex-centric
paradigm, and its implementation on Giraph, a popular platform for distributed
graph algorithms. Experiments show the effectiveness and the scalability of the
approach. Using an inexpensive cloud computing service of Amazon, we draw
graphs with ten million edges in about 60 minutes.Comment: Appears in the Proceedings of the 24th International Symposium on
Graph Drawing and Network Visualization (GD 2016
Advanced Multilevel Node Separator Algorithms
A node separator of a graph is a subset S of the nodes such that removing S
and its incident edges divides the graph into two disconnected components of
about equal size. In this work, we introduce novel algorithms to find small
node separators in large graphs. With focus on solution quality, we introduce
novel flow-based local search algorithms which are integrated in a multilevel
framework. In addition, we transfer techniques successfully used in the graph
partitioning field. This includes the usage of edge ratings tailored to our
problem to guide the graph coarsening algorithm as well as highly localized
local search and iterated multilevel cycles to improve solution quality even
further. Experiments indicate that flow-based local search algorithms on its
own in a multilevel framework are already highly competitive in terms of
separator quality. Adding additional local search algorithms further improves
solution quality. Our strongest configuration almost always outperforms
competing systems while on average computing 10% and 62% smaller separators
than Metis and Scotch, respectively
Recent Advances in Graph Partitioning
We survey recent trends in practical algorithms for balanced graph
partitioning together with applications and future research directions
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