Title :
Estimating sensor population via probabilistic sequential polling
Author :
Leshem, Amir ; Tong, Lang
Author_Institution :
Sch. of Eng., Bar-Ilan Univ., Ramat-Gan, Israel
fDate :
5/1/2005 12:00:00 AM
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(log2N) sensor transmissions and a total of O((log2N)2) polls to achieve an arbitrarily predetermined level of accuracy.
Keywords :
mobile radio; protocols; sequential estimation; wireless sensor networks; PSPP; large-scale sensor network; mobile access point; probabilistic sequential polling protocol; sensor population estimation; Access protocols; Broadcasting; Data mining; Energy efficiency; Estimation error; Large-scale systems; Sampling methods; Sensor phenomena and characterization; Sensor systems; Time division multiple access; Estimation; polling; probabilistic algorithms; sensor network with mobile access (SENMA); sensor networks;
Journal_Title :
Signal Processing Letters, IEEE
DOI :
10.1109/LSP.2005.845595
