Subexponential-time framework for optimal embeddings of graphs in integer lattices
(2004) 9th Scandinavian Workshop on Algorithm Theory 3111. p.248-259- Abstract
- We present a general framework for computing various optimal embeddings of undirected and directed connected graphs in two and multi-dimensional integer lattices in time sub-exponential either in the minimum number n of lattice points used by such optimal embeddings or in the budget upper bound b on the number of lattice points that may be used in an embedding. The sub-exponential upper bounds in the two dimensional case and d-dimensional case are respectively of the form 2(O(rootln log n)), 2(Orootlb log b)) and 2(n)(O(dl1/d) ((d-1)/d)(log n)),2(O(dl l/d(d-1)/d) (log b),) where l stands for the degree of the allowed overlap. For the problem of minimum total edge length planar or multi-dimensional embedding or layout of a graph and the... (More)
- We present a general framework for computing various optimal embeddings of undirected and directed connected graphs in two and multi-dimensional integer lattices in time sub-exponential either in the minimum number n of lattice points used by such optimal embeddings or in the budget upper bound b on the number of lattice points that may be used in an embedding. The sub-exponential upper bounds in the two dimensional case and d-dimensional case are respectively of the form 2(O(rootln log n)), 2(Orootlb log b)) and 2(n)(O(dl1/d) ((d-1)/d)(log n)),2(O(dl l/d(d-1)/d) (log b),) where l stands for the degree of the allowed overlap. For the problem of minimum total edge length planar or multi-dimensional embedding or layout of a graph and the problem of an optimal protein folding in the so called HP model we obtain the upper bounds in terms of n. Note that in case of protein folding n is also the size of the input. The list of problems for which we can derive the upper bounds in terms of b includes among other things: 1. a minimum area planar embedding or layout of a graph, 2. a minimum bend planar or three dimensional embedding or layout, 3. a minimum maximum edge length planar or three dimensional embedding or layout. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/272609
- author
- Dessmark, Anders LU ; Lingas, Andrzej LU and Lundell, Eva-Marta LU
- organization
- publishing date
- 2004
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- host publication
- Algorithm Theory - SWAT 2004/Lecture Notes in Computer Science
- volume
- 3111
- pages
- 248 - 259
- publisher
- Springer
- conference name
- 9th Scandinavian Workshop on Algorithm Theory
- conference location
- Humlebaek, Denmark
- conference dates
- 2004-07-08 - 2004-07-10
- external identifiers
-
- wos:000222682500022
- scopus:35048818561
- ISSN
- 1611-3349
- 0302-9743
- ISBN
- 978-3-540-22339-9
- DOI
- 10.1007/b98413
- project
- VR 2002-4049
- language
- English
- LU publication?
- yes
- id
- 46227d3a-4555-4feb-93a0-df9b04a5fb60 (old id 272609)
- date added to LUP
- 2016-04-01 12:11:23
- date last changed
- 2024-01-08 11:36:16
@inproceedings{46227d3a-4555-4feb-93a0-df9b04a5fb60,
abstract = {{We present a general framework for computing various optimal embeddings of undirected and directed connected graphs in two and multi-dimensional integer lattices in time sub-exponential either in the minimum number n of lattice points used by such optimal embeddings or in the budget upper bound b on the number of lattice points that may be used in an embedding. The sub-exponential upper bounds in the two dimensional case and d-dimensional case are respectively of the form 2(O(rootln log n)), 2(Orootlb log b)) and 2(n)(O(dl1/d) ((d-1)/d)(log n)),2(O(dl l/d(d-1)/d) (log b),) where l stands for the degree of the allowed overlap. For the problem of minimum total edge length planar or multi-dimensional embedding or layout of a graph and the problem of an optimal protein folding in the so called HP model we obtain the upper bounds in terms of n. Note that in case of protein folding n is also the size of the input. The list of problems for which we can derive the upper bounds in terms of b includes among other things: 1. a minimum area planar embedding or layout of a graph, 2. a minimum bend planar or three dimensional embedding or layout, 3. a minimum maximum edge length planar or three dimensional embedding or layout.}},
author = {{Dessmark, Anders and Lingas, Andrzej and Lundell, Eva-Marta}},
booktitle = {{Algorithm Theory - SWAT 2004/Lecture Notes in Computer Science}},
isbn = {{978-3-540-22339-9}},
issn = {{1611-3349}},
language = {{eng}},
pages = {{248--259}},
publisher = {{Springer}},
title = {{Subexponential-time framework for optimal embeddings of graphs in integer lattices}},
url = {{http://dx.doi.org/10.1007/b98413}},
doi = {{10.1007/b98413}},
volume = {{3111}},
year = {{2004}},
}