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The dynamic behavior of a data dissemination protocol for network programming at scale
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Source Conference On Embedded Networked Sensor Systems archive
Proceedings of the 2nd international conference on Embedded networked sensor systems table of contents
Baltimore, MD, USA
SESSION: Programming table of contents
Pages: 81 - 94  
Year of Publication: 2004
ISBN:1-58113-879-2
Authors
Jonathan W. Hui  University of California at Berkeley
David Culler  University of California at Berkeley
Sponsors
SIGARCH: ACM Special Interest Group on Computer Architecture
SIGBED: ACM Special Interest Group on Embedded Systems
ACM: Association for Computing Machinery
SIGMOBILE: ACM Special Interest Group on Mobility of Systems, Users, Data and Computing
SIGCOMM: ACM Special Interest Group on Data Communication
SIGMETRICS: ACM Special Interest Group on Measurement and Evaluation
SIGOPS: ACM Special Interest Group on Operating Systems
Publisher
ACM  New York, NY, USA
Bibliometrics
Downloads (6 Weeks): 31,   Downloads (12 Months): 270,   Citation Count: 101
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ABSTRACT

To support network programming, we present Deluge, a reliable data dissemination protocol for propagating large data objects from one or more source nodes to many other nodes over a multihop, wireless sensor network. Deluge builds from prior work in density-aware, epidemic maintenance protocols. Using both a real-world deployment and simulation, we show that Deluge can reliably disseminate data to all nodes and characterize its overall performance. On Mica2-dot nodes, Deluge can push nearly 90 bytes/second, one-ninth the maximum transmission rate of the radio supported under TinyOS. Control messages are limited to 18% of all transmissions. At scale, the protocol exposes interesting propagation dynamics only hinted at by previous dissemination work. A simple model is also derived which describes the limits of data propagation in wireless networks. Finally, we argue that the rates obtained for dissemination are inherently lower than that for single path propagation. It appears very hard to significantly improve upon the rate obtained by Deluge and we identify establishing a tight lower bound as an open problem.


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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D. Ganesan, B. Krishnamachari, A. Woo, D. Culler, D. Estrin, and S. Wicker. Complex behavior at scale: An experimental study of low-power wireless sensor networks. Technical Report UCLA/CSD-TR 02-0013, UCLA, 2002.
 
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J. Jeong, S. Kim, and A. Broad. Network Reprogramming. University of California at Berkeley, Berkeley, CA, USA, August 2003.
 
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P. Levis, N. Patel, S. Shenker, and D. Culler. Trickle: A self-regulating algorithm for code propagation and maintenance in wireless sensor networks. Technical report, University of California at Berkeley, 2004.
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F. Stann and J. Heidemann. RMST: Reliable data transport in sensor networks. In Proceedings of the First International Workshop on Sensor Net Protocols and Applications, pages 102--112, Anchorage, Alaska, USA, April 2003. IEEE.
 
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T. Stathopoulos, J. Heidemann, and D. Estrin. A remote code update mechanism for wireless sensor networks. Technical report, UCLA, Los Angeles, CA, USA, 2003.
 
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R. Szewczyk, J. Polastre, A. Mainwaring, and D. Culler. Lessons from a sensor network expedition. In Proceedings of the First European Workshop on Sensor Networks (EWSN), Berlin, Germany, Jan. 2004.
 
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University of California, Berkeley. Smote testbed. http://smote.cs.berkeley.edu/.
 
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University of California, Berkeley. Mica2-dot schematics.
 
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University of California, Berkeley. Tinyos. http://www.tinyos.net/, 2004.
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CITED BY  101
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Collaborative Colleagues:
Jonathan W. Hui: colleagues
David Culler: colleagues