Estimating sensor population via probabilistic sequential polling

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(log/sub 2/N) sensor transmissions and a total of O((log/sub 2/N)/sup 2/) polls to achieve an arbitrarily predetermined level of accuracy.

[1]  Lang Tong,et al.  Good-Turing estimation of the number of operating sensors: a large deviations analysis , 2004, 2004 IEEE International Conference on Acoustics, Speech, and Signal Processing.

[2]  I. Good.  THE POPULATION FREQUENCIES OF SPECIES AND THE ESTIMATION OF POPULATION PARAMETERS , 1953 .

[3]  Noga Alon,et al.  The Probabilistic Method, Second Edition , 2004 .

[4]  Lang Tong,et al.  Estimation of the number of operating sensors in large-scale sensor networks with mobile access , 2006, IEEE Transactions on Signal Processing.

[5]  Lang Tong,et al.  Estimation of the number of operating sensors in sensor network , 2003, The Thrity-Seventh Asilomar Conference on Signals, Systems & Computers, 2003.

[6]  Noga Alon,et al.  The Probabilistic Method , 2015, Fundamentals of Ramsey Theory.

[7]  Lang Tong,et al.  Sensor networks with mobile agents , 2003, IEEE Military Communications Conference, 2003. MILCOM 2003..