Distributed Detection/Isolation Procedures for Quickest Event Detection in Large Extent Wireless Sensor Networks

TL;DR

This paper develops distributed detection and localization procedures for stationary events in large wireless sensor networks, achieving near-optimal detection delays while satisfying false alarm and false isolation constraints.

Contribution

It introduces novel distributed algorithms based on local CUSUM fusion for event detection and localization, with proven bounds on detection delay and false alarm/isolation probabilities.

Findings

Distributed procedures achieve asymptotic optimality in detection delay.

Bounds on false alarm and false isolation probabilities are established.

Detection delay scales with target performance parameters similarly to centralized methods.

Abstract

We study a problem of distributed detection of a stationary point event in a large extent wireless sensor network ($\wsn$), where the event influences the observations of the sensors only in the vicinity of where it occurs. An event occurs at an unknown time and at a random location in the coverage region (or region of interest ($\ROI$)) of the $\wsn$. We consider a general sensing model in which the effect of the event at a sensor node depends on the distance between the event and the sensor node; in particular, in the Boolean sensing model, all sensors in a disk of a given radius around the event are equally affected. Following the prior work reported in \cite{nikiforov95change_isolation}, \cite{nikiforov03lower-bound-for-det-isolation}, \cite{tartakovsky08multi-decision}, {\em the problem is formulated as that of detecting the event and locating it to a subregion of the $\ROI$ as early as possible under the constraints that the average run length to false alarm ($\tfa$) is bounded below by $\gamma$, and the probability of false isolation ($\pfi$) is bounded above by $\alpha$}, where $\gamma$ and $\alpha$ are target performance requirements. In this setting, we propose distributed procedures for event detection and isolation (namely $\mx$, $\all$, and $\hall$), based on the local fusion of $\CUSUM$s at the sensors. For these procedures, we obtain bounds on the maximum mean detection/isolation delay ($\add$), and on $\tfa$ and $\pfi$, and thus provide an upper bound on $\add$ as $\min\{\gamma,1/\alpha\} \to \infty$. For the Boolean sensing model, we show that an asymptotic upper bound on the maximum mean detection/isolation delay of our distributed procedure scales with $\gamma$ and $\alpha$ in the same way as the asymptotically optimal centralised procedure \cite{nikiforov03lower-bound-for-det-isolation}.