ACM Home Page
Please provide us with feedback. Feedback
On the pitfalls of geographic face routing
Full text PdfPdf (1.24 MB)
Source Workshop on Discrete Algothrithms and Methods for MOBILE Computing and Communications archive
Proceedings of the 2005 joint workshop on Foundations of mobile computing table of contents
Cologne, Germany
SESSION: Location-aware mechanisms table of contents
Pages: 34 - 43  
Year of Publication: 2005
ISBN:1-59593-092-2
Authors
Young-Jin Kim  University of Southern California
Ramesh Govindan  University of Southern California
Brad Karp  Intel Research/CMU
Scott Shenker  UCB/ICSI
Sponsors
SIGMOBILE: ACM Special Interest Group on Mobility of Systems, Users, Data and Computing
ACM: Association for Computing Machinery
Publisher
ACM  New York, NY, USA
Bibliometrics
Downloads (6 Weeks): 23,   Downloads (12 Months): 64,   Citation Count: 10
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/10.1145/1080810.1080818
What is a DOI?

ABSTRACT

Geographic face routing algorithms have been widely studied in the literature [1, 8, 13]. All face routing algorithms rely on two primitives: planarization and face traversal. The former computes a planar subgraph of the underlying wireless connectivity graph, while the latter defines a consistent forwarding mechanism for routing around "voids." These primitives are known to be provably correct under the idealized unit-disk graph assumption, where nodes are assumed to be connected if and only if they are within a certain distance from each other.In this paper we classify the ways in which existing planarization techniques fail with realistic, non-ideal radios. We also demonstrate the consequences of these pathologies on reachability between node pairs in a real wireless testbed. We then examine the various face traversal rules described in the literature, and identify those [12, 16] that are robust to violations of the unit-disk graph assumption.


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
Finn, G. Routing and addressing problems in large metropolitan-scale internetworks. Tech. Rep. ISI/RR-87-180, USC/Information Sciences Institute, Mar. 1987.
 
3
Gabriel, K., and Sokal, R. A new statistical approach to geographic variation analysis. Systematic Zoology 18 (1969), 259--278.
4
5
 
6
 
7
Karp, B. Challenges in geographic routing: Sparse networks, obstacles, and traffic provisioning. Presentation at the DIMACS Workshop on Pervasive Networking, May 2001.
8
 
9
Kim, Y.-J., Govindan, R., Karp, B., and Shenker, S. Geographic routing made practical. In Proc. USENIX Symposium on Network Systems Design and Implementation (Boston, Massachusetts, USA, May 2005), USENIX.
 
10
Kleinrock, L., and Takagi, H. Optimal transmission ranges for randomly distributed packet radio terminals. IEEE Trans. Comm. 32, 3 (1984), 246--257.
11
 
12
Kranakis, E., Singh, H., and Urrutia, J. Compass routing on geometric networks. In Proc. 11th Canadian Conference on Computational Geometry, Aug. 1999.
13
14
15
16
17
18
19
20
21
22
 
23
Toussaint, G. The relative neighborhood graph of a finite planar set. Pattern Recognition 12, 4 (1980), 261--268.
24
25
26

CITED BY  10

Collaborative Colleagues:
Young-Jin Kim: colleagues
Ramesh Govindan: colleagues
Brad Karp: colleagues
Scott Shenker: colleagues