首页 | 本学科首页   官方微博 | 高级检索  
     


Plane Embeddings of Planar Graph Metrics
Authors:MohammadHossein Bateni  Erik D. Demaine  MohammadTaghi Hajiaghayi  Mohammad Moharrami
Affiliation:(1) Department of Computer Engineering, Sharif University of Technology, Azadi St., Tehren, Iran;(2) Computer Science and Artificial Intelligence Laboratory, MIT, 32 Vassar St., Cambridge, MA 02139, USA;(3) Department of Computer Science, Carnegie Mellon University, 4109 Wean Hall, Pittsburgh, PA 15213, USA
Abstract:Embedding metrics into constant-dimensional geometric spaces, such as the Euclidean plane, is relatively poorly understood. Motivated by applications in visualization, ad-hoc networks, and molecular reconstruction, we consider the natural problem of embedding shortest-path metrics of unweighted planar graphs (planar graph metrics) into the Euclidean plane. It is known that, in the special case of shortest-path metrics of trees, embedding into the plane requires $Theta(sqrt n)$ distortion in the worst case [M1], [BMMV], and surprisingly, this worst-case upper bound provides the best known approximation algorithm for minimizing distortion. We answer an open question posed in this work and highlighted by Matousek [M3] by proving that some planar graph metrics require $Omega(n^{2/3})$ distortion in any embedding into the plane, proving the first separation between these two types of graph metrics. We also prove that some planar graph metrics require $Omega(n)$ distortion in any crossing-free straight-line embedding into the plane, suggesting a separation between low-distortion plane embedding and the well-studied notion of crossing-free straight-line planar drawings. Finally, on the upper-bound side, we prove that all outerplanar graph metrics can be embedded into the plane with $O(sqrt n)$ distortion, generalizing the previous results on trees (both the worst-case bound and the approximation algorithm) and building techniques for handling cycles in plane embeddings of graph metrics.
Keywords:
本文献已被 SpringerLink 等数据库收录!
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号