48,516 research outputs found
The Parameterized Complexity of Centrality Improvement in Networks
The centrality of a vertex v in a network intuitively captures how important
v is for communication in the network. The task of improving the centrality of
a vertex has many applications, as a higher centrality often implies a larger
impact on the network or less transportation or administration cost. In this
work we study the parameterized complexity of the NP-complete problems
Closeness Improvement and Betweenness Improvement in which we ask to improve a
given vertex' closeness or betweenness centrality by a given amount through
adding a given number of edges to the network. Herein, the closeness of a
vertex v sums the multiplicative inverses of distances of other vertices to v
and the betweenness sums for each pair of vertices the fraction of shortest
paths going through v. Unfortunately, for the natural parameter "number of
edges to add" we obtain hardness results, even in rather restricted cases. On
the positive side, we also give an island of tractability for the parameter
measuring the vertex deletion distance to cluster graphs
Wrapping layered graphs
We present additions to the widely-used layout method for directed acyclic graphs of Sugiyama et al. [16] that allow to better utilize a prescribed drawing area. The method itself partitions the graph's nodes into layers. When drawing from top to bottom, the number of layers directly impacts the height of a resulting drawing and is bound from below by the graph's longest path. As a consequence, the drawings of certain graphs are significantly taller than wide, making it hard to properly display them on a medium such as a computer screen without scaling the graph's elements down to illegibility. We address this with the Wrapping Layered Graphs Problem (WLGP), which seeks for cut indices that split a given layering into chunks that are drawn side-by-side with a preferably small number of edges wrapping backwards. Our experience and a quantitative evaluation indicate that the proposed wrapping allows an improved presentation of narrow graphs, which occur frequently in practice and of which the internal compiler representation SCG is one example
Incremental Cycle Detection, Topological Ordering, and Strong Component Maintenance
We present two on-line algorithms for maintaining a topological order of a
directed -vertex acyclic graph as arcs are added, and detecting a cycle when
one is created. Our first algorithm handles arc additions in
time. For sparse graphs (), this bound improves the best previous
bound by a logarithmic factor, and is tight to within a constant factor among
algorithms satisfying a natural {\em locality} property. Our second algorithm
handles an arbitrary sequence of arc additions in time. For
sufficiently dense graphs, this bound improves the best previous bound by a
polynomial factor. Our bound may be far from tight: we show that the algorithm
can take time by relating its performance to a
generalization of the -levels problem of combinatorial geometry. A
completely different algorithm running in time was given
recently by Bender, Fineman, and Gilbert. We extend both of our algorithms to
the maintenance of strong components, without affecting the asymptotic time
bounds.Comment: 31 page
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