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GHT: a geographic hash table for data-centric storage
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Source International Workshop on Wireless Sensor Networks and Applications archive
Proceedings of the 1st ACM international workshop on Wireless sensor networks and applications table of contents
Atlanta, Georgia, USA
SESSION: Applications and OS table of contents
Pages: 78 - 87  
Year of Publication: 2002
ISBN:1-58113-589-0
Authors
Sylvia Ratnasamy  ICIR/ICSI, Berkeley, CA
Brad Karp  ICIR/ICSI, Berkeley, CA
Li Yin  Berkeley EECS, Berkeley, CA
Fang Yu  Berkeley EECS, Berkeley, CA
Deborah Estrin  UCLA Comp. Sci., LA, CA
Ramesh Govindan  USC Comp. Sci., LA, CA
Scott Shenker  ICIR/ICSI, Berkeley, CA
Sponsors
ACM: Association for Computing Machinery
SIGMOBILE: ACM Special Interest Group on Mobility of Systems, Users, Data and Computing
Publisher
ACM  New York, NY, USA
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Downloads (6 Weeks): 21,   Downloads (12 Months): 129,   Citation Count: 120
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ABSTRACT

Making effective use of the vast amounts of data gathered by large-scale sensor networks will require scalable, self-organizing, and energy-efficient data dissemination algorithms. Previous work has identified data-centric routing as one such method. In an asso-ciated position paper [23], we argue that a companion method, data-centric storage (DCS), is also a useful approach. Under DCS, sensed data are stored at a node determined by the name associated with the sensed data. In this paper, we describe GHT, a Geographic Hash Table system for DCS on sensornets. GHT hashes keys into geographic coordi-nates, and stores a key-value pair at the sensor node geographically nearest the hash of its key. The system replicates stored data lo-cally to ensure persistence when nodes fail. It uses an efficient consistency protocol to ensure that key-value pairs are stored at the appropriate nodes after topological changes. And it distributes load throughout the network using a geographic hierarchy. We evaluate the performance of GHT as a DCS system in simulation against two other dissemination approaches. Our results demonstrate that GHT is the preferable approach for the application workloads predicted in [23], offers high data availability, and scales to large sensornet deployments, even when nodes fail or are mobile.


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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S. Shenker, S. Ratnasamy, B. Karp, R. Govindan, and D. Estrin, Data-centric storage in sensornets, Under submission to ACM SIGCOMM HotNets, Jul. 2002.
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CITED BY  120

Collaborative Colleagues:
Sylvia Ratnasamy: colleagues
Brad Karp: colleagues
Li Yin: colleagues
Fang Yu: colleagues
Deborah Estrin: colleagues
Ramesh Govindan: colleagues
Scott Shenker: colleagues