ACM Home Page
Please provide us with feedback. Feedback
What can be approximated locally?: case study: dominating sets in planar graphs
Full text PdfPdf (972 KB)
Source
ACM Symposium on Parallel Algorithms and Architectures archive
Proceedings of the twentieth annual symposium on Parallelism in algorithms and architectures table of contents
Munich, Germany
SESSION: Algorithms on graphs table of contents
Pages 46-54  
Year of Publication: 2008
ISBN:978-1-59593-973-9
Authors
Christoph Lenzen  ETH Zurich, Switzerland
Yvonne Anne Oswald  ETH Zurich, Switzerland
Roger Wattenhofer  ETH Zurich, Switzerland
Sponsors
ACM: Association for Computing Machinery
SIGACT: ACM Special Interest Group on Algorithms and Computation Theory
SIGARCH: ACM Special Interest Group on Computer Architecture
Publisher
ACM  New York, NY, USA
Bibliometrics
Downloads (6 Weeks): 13,   Downloads (12 Months): 96,   Citation Count: 3
Additional Information:

abstract   references   cited by   index terms   collaborative colleagues  

Tools and Actions: Request Permissions Request Permissions    Review this Article  
DOI Bookmark: Use this link to bookmark this Article: http://doi.acm.org/10.1145/1378533.1378540
What is a DOI?

ABSTRACT

Whether local algorithms can compute constant approximations of NP-hard problems is of both practical and theoretical interest. So far, no algorithms achieving this goal are known, as either the approximation ratio or the running time exceed O(1), or the nodes are provided with non-trivial additional information. In this paper, we present the first distributed algorithm approximating a minimum dominating set on a planar graph within a constant factor in constant time. Moreover, the nodes do not need any additional information.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
1
 
2
 
3
 
4
A. Czygrinow, M. Hanckowiak, and E. Szymanska. Distributed Approximation Algorithms for Planar Graphs. In Proceedings of the 6th Italian Conference on Algorithms and Complexity (CIAC), 2006.
 
5
P. Floréen, P. Kaski, T. Musto, and J. Suomela. Local Approximation Algorithms for Scheduling Problems in Sensor Networks. In Proceedings of the 3rd International Workshop on Algorithmic Aspects of Wireless Sensor Networks (Algosensors), 2007.
 
6
P. Floréen, P. Kaski, and J. Suomela. A distributed approximation scheme for sleep scheduling in sensor networks. In Proc. 4th Annual IEEE Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks (SECON, San Diego, CA, USA, June 2007), pages 152--161, Piscataway, NJ, USA, 2007. IEEE.
 
7
P. Fraigniaud, C. Gavoille, D. Ilcinkas, and A. Pelc. Distributed computing with advice: Information sensitivity of graph coloring. In 34th International Colloquium onAutomata, Languages and Programming (ICALP), pages 231--242, 2007.
8
9
 
10
11
 
12
 
13
 
14
F. Kuhn, T. Moscibroda, T. Nieberg, and R. Wattenhofer. Fast Deterministic Distributed Maximal Independent Set Computation on Growth-Bounded Graphs. In Proc. 19th International Symposium on Distributed Computing (DISC), 2005.
15
16
17
18
 
19
 
20
 
21
 
22
 
23
J. Schneider and R. Wattenhofer. A Log-Star Distributed Maximal Independent Set Algorithm for Growth-Bounded Graphs. In 27th Annual ACM SIGACT-SIGOPS Symposium on Principles of Distributed Computing, August 2008.
 
24
A. Wiese and E. Kranakis. Local PTAS for Independent Set and Vertex Cover in Location Aware Unit Disk Graphs. In Proceedings of the 4th IEEE/ACM International Conference on Distributed Computing in Sensor Systems (DCOSS), June 2008.


Collaborative Colleagues:
Christoph Lenzen: colleagues
Yvonne Anne Oswald: colleagues
Roger Wattenhofer: colleagues