Estimating sensor population via probabilistic sequential polling

Amir Leshem; Lang Tong

doi:10.1109/LSP.2005.845595

Estimating sensor population via probabilistic sequential polling

Amir Leshem^*, Lang Tong

^*Corresponding author for this work

Research output: Contribution to journal › Article › peer-review

16 Scopus citations

Abstract

A probabilistic sequential polling protocol (PSPP) is presented for the estimation of the sensor population in a large-scale sensor network with a mobile access point. It is shown that PSPP requires O(log₂ N) sensor transmissions and a total of O ((log₂ N)²) polls to achieve an arbitrarily predetermined level of accuracy.

Original language	English
Pages (from-to)	395-398
Number of pages	4
Journal	IEEE Signal Processing Letters
Volume	12
Issue number	5
DOIs	https://doi.org/10.1109/LSP.2005.845595
State	Published - May 2005
Externally published	Yes

Bibliographical note

Funding Information:
Manuscript received August 8, 2004; revised November 30, 2004. This work was supported in part by he Multidisciplinary University Research Initiative (MURI) by the Army Research Laboratory CTA on Communication and Networks under Grant DAAD19-01-2-0011. The associate editor coordinating the review of this manuscript and approving it for publication was Dr. Erchin Serpedin.

Keywords

Estimation
Polling
Probabilistic algorithms
Sensor network with mobile access (SENMA)
Sensor networks

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10.1109/LSP.2005.845595

Cite this

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author = "Amir Leshem and Lang Tong",

note = "Funding Information: Manuscript received August 8, 2004; revised November 30, 2004. This work was supported in part by he Multidisciplinary University Research Initiative (MURI) by the Army Research Laboratory CTA on Communication and Networks under Grant DAAD19-01-2-0011. The associate editor coordinating the review of this manuscript and approving it for publication was Dr. Erchin Serpedin.",

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AB - A probabilistic sequential polling protocol (PSPP) is presented for the estimation of the sensor population in a large-scale sensor network with a mobile access point. It is shown that PSPP requires O(log2 N) sensor transmissions and a total of O ((log2 N)2) polls to achieve an arbitrarily predetermined level of accuracy.

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KW - Polling

KW - Probabilistic algorithms

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Estimating sensor population via probabilistic sequential polling

Abstract

Bibliographical note

Keywords

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