A note on optimal area algorithms for upward drawings of binary trees
Computational Geometry: Theory and Applications
A better heuristic for orthogonal graph drawings
Computational Geometry: Theory and Applications
Interactive Orthogonal Graph Drawing
IEEE Transactions on Computers
Drawing graphs
Reductions in streaming algorithms, with an application to counting triangles in graphs
SODA '02 Proceedings of the thirteenth annual ACM-SIAM symposium on Discrete algorithms
Straight-Line Drawings of Binary Trees with Linear Area and Arbitrary Aspect Ratio
GD '02 Revised Papers from the 10th International Symposium on Graph Drawing
The Minimum Area of Convex Lattice n-Gons
Combinatorica
Data streams: algorithms and applications
Foundations and Trends® in Theoretical Computer Science
Straight-line drawings of general trees with linear area and arbitrary aspect ratio
ICCSA'03 Proceedings of the 2003 international conference on Computational science and its applications: PartIII
Visual analysis of news streams with article threads
Proceedings of the First International Workshop on Novel Data Stream Pattern Mining Techniques
Drawing trees in a streaming model
Information Processing Letters
Graph drawing in the cloud: privately visualizing relational data using small working storage
GD'12 Proceedings of the 20th international conference on Graph Drawing
StreamEB: stream edge bundling
GD'12 Proceedings of the 20th international conference on Graph Drawing
Hi-index | 0.00 |
We introduce a data stream model of computation for Graph Drawing, where a source produces a graph one edge at a time. When an edge is produced, it is immediately drawn and its drawing can not be altered. The drawing has an image persistence, that controls the lifetime of edges. If the persistence is k, an edge remains in the drawing for the time spent by the source to generate k edges, then it fades away. In this model we study the area requirement of planar straight-line grid drawings of trees, with different streaming orders, layout models, and quality criteria. We assess the output quality of the presented algorithms by computing the competitive ratio with respect to the best known offline algorithms.