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Understanding packet delivery performance in dense wireless sensor networks
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Source Conference On Embedded Networked Sensor Systems archive
Proceedings of the 1st international conference on Embedded networked sensor systems table of contents
Los Angeles, California, USA
SESSION: Networking experience table of contents
Pages: 1 - 13  
Year of Publication: 2003
ISBN:1-58113-707-9
Authors
Jerry Zhao  University of Southern California, Los Angeles, CA
Ramesh Govindan  University of Southern California, Los Angeles, CA
Sponsors
SIGGRAPH: ACM Special Interest Group on Computer Graphics and Interactive Techniques
ACM: Association for Computing Machinery
SIGCOMM: ACM Special Interest Group on Data Communication
SIGMOBILE: ACM Special Interest Group on Mobility of Systems, Users, Data and Computing
SIGMETRICS: ACM Special Interest Group on Measurement and Evaluation
SIGOPS: ACM Special Interest Group on Operating Systems
Publisher
ACM  New York, NY, USA
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Downloads (6 Weeks): 41,   Downloads (12 Months): 353,   Citation Count: 152
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ABSTRACT

Wireless sensor networks promise fine-grain monitoring in a wide variety of environments. Many of these environments (e.g., indoor environments or habitats) can be harsh for wireless communication. From a networking perspective, the most basic aspect of wireless communication is the packet delivery performance: the spatio-temporal characteristics of packet loss, and its environmental dependence. These factors will deeply impact the performance of data acquisition from these networks.In this paper, we report on a systematic medium-scale (up to sixty nodes) measurement of packet delivery in three different environments: an indoor office building, a habitat with moderate foliage, and an open parking lot. Our findings have interesting implications for the design and evaluation of routing and medium-access protocols for sensor networks.


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  152

Collaborative Colleagues:
Jerry Zhao: colleagues
Ramesh Govindan: colleagues