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Analysis of a cone-based distributed topology control algorithm for wireless multi-hop networks
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Source Annual ACM Symposium on Principles of Distributed Computing archive
Proceedings of the twentieth annual ACM symposium on Principles of distributed computing table of contents
Newport, Rhode Island, United States
Pages: 264 - 273  
Year of Publication: 2001
ISBN:1-58113-383-9
Authors
Li Li  Cornell Univ., Ithaca, NY
Joseph Y. Halpern  Cornell Univ., Ithaca, NY
Paramvir Bahl  Microsoft Research
Yi-Min Wang  Microsoft Research
Roger Wattenhofer  Microsoft Research
Sponsors
SIGACT: ACM Special Interest Group on Algorithms and Computation Theory
SIGOPS: ACM Special Interest Group on Operating Systems
Publisher
ACM  New York, NY, USA
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Downloads (6 Weeks): 7,   Downloads (12 Months): 33,   Citation Count: 70
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ABSTRACT

The topology of a wireless multi-hop network can be controlled by varying the transmission power at each node. In this paper, we give a detailed analysis of a cone-based distributed topology control algorithm. This algorithm, introduced in [16], does not assume that nodes have GPS information available; rather it depends only on directional information. Roughly speaking, the basic idea of the algorithm is that a node u transmits with the minimum power pu, &agr; required to ensure that in every cone of degree &agr; around u, there is some node that u can reach with power pu, &agr;. We show that taking &agr; = 5&pgr;/6 is a necessary and sufficient condition to guarantee that network connectivity is preserved. More precisely, if there is a path from s to t when every node communicates at maximum power then, if &agr; ⪇ 5&pgr;/6, there is still a path in the smallest symmetric graph G&agr; containing all edges (u, v) such that u can communicate with v using power pu, &agr;. On the other hand, if &agr; > 5&pgr;/6, connectivity is not necessarily preserved. We also propose a set of optimizations that further reduce power consumption and prove that they retain network connectivity. Dynamic reconfiguration in the presence of failures and mobility is also discussed. Simulation results are presented to demonstrate the effectiveness of the algorithm and the optimizations.


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.

 
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CITED BY  70

Collaborative Colleagues:
Li Li: colleagues
Joseph Y. Halpern: colleagues
Paramvir Bahl: colleagues
Yi-Min Wang: colleagues
Roger Wattenhofer: colleagues