Estimation of the number of operating sensors in large-scale sensor networks with mobile access

This paper investigates the estimation of the number of operating sensors in a sensor network in which the data collection is made by a mobile access point. In this paper, an estimator based on the Good-Turing estimator of the missing mass is proposed and it is generalized to other related problems such as the estimation of the distribution of energy available at sensors. The estimator is analyzed using the theory of large deviations. Closed-form bounds on the large deviation exponent are presented and confidence intervals for the estimator are characterized.

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

[2]  Phil Whiting,et al.  Large deviation asymptotics for occupancy problems , 2004 .

[3]  Thomas M. Cover,et al.  Elements of Information Theory , 2005 .

[4]  David A. McAllester,et al.  On the Convergence Rate of Good-Turing Estimators , 2000, COLT.

[5]  S. Resnick A Probability Path , 1999 .

[6]  Howard G. Tucker,et al.  Confidence intervals for the number of unseen types , 1998 .

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

[8]  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.

[9]  Warren W. Esty,et al.  The Efficiency of Good's Nonparametric Coverage Estimator , 1986 .

[10]  Lang Tong,et al.  Sensor networks with mobile access: optimal random access and coding , 2004, IEEE Journal on Selected Areas in Communications.

[11]  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.

[12]  Alon Orlitsky,et al.  Always Good Turing: Asymptotically Optimal Probability Estimation , 2003, Science.