Drawing trees in a streaming model

Binucci, C; Brandes, U; Di Battista, G; Didimo, W; Gaertler, M; Palladino, P; Patrignani, M; Symvonis, A; Zweig, K

dc.contributor.author	Binucci, C	en
dc.contributor.author	Brandes, U	en
dc.contributor.author	Di Battista, G	en
dc.contributor.author	Didimo, W	en
dc.contributor.author	Gaertler, M	en
dc.contributor.author	Palladino, P	en
dc.contributor.author	Patrignani, M	en
dc.contributor.author	Symvonis, A	en
dc.contributor.author	Zweig, K	en
dc.date.accessioned	2014-03-01T02:52:39Z
dc.date.available	2014-03-01T02:52:39Z
dc.date.issued	2010	en
dc.identifier.issn	03029743	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/35972
dc.subject.other	Area requirement	en
dc.subject.other	Competitive ratio	en
dc.subject.other	Data stream model	en
dc.subject.other	Graph drawing	en
dc.subject.other	Grid drawing	en
dc.subject.other	Layout model	en
dc.subject.other	Off-line algorithm	en
dc.subject.other	Output quality	en
dc.subject.other	Quality criteria	en
dc.subject.other	Streaming model	en
dc.subject.other	Time spent	en
dc.subject.other	Computation theory	en
dc.subject.other	Drawing (graphics)	en
dc.subject.other	Edge detection	en
dc.title	Drawing trees in a streaming model	en
heal.type	conferenceItem	en
heal.identifier.primary	10.1007/978-3-642-11805-0_28	en
heal.identifier.secondary	http://dx.doi.org/10.1007/978-3-642-11805-0_28	en
heal.publicationDate	2010	en
heal.abstract	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. © 2010 Springer-Verlag.	en
heal.journalName	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)	en
dc.identifier.doi	10.1007/978-3-642-11805-0_28	en
dc.identifier.volume	5849 LNCS	en
dc.identifier.spage	292	en
dc.identifier.epage	303	en