Abstract
We consider distributed detection in a clustered wireless sensor network (WSN) deployed randomly in a large field for the purpose of intrusion detection. The WSN is modeled by a homogeneous Poisson point process. The sensor nodes (SNs) compute local decisions about the intruder’s presence and send them to the cluster heads (CHs). A stochastic geometry framework is employed to derive the optimal cluster-based fusion rule (OCR), which is a weighted average of the local decision sum of each cluster. Interestingly, this structure reduces the effect of false alarm on the detection performance. Moreover, a generalized likelihood ratio test (GLRT) for cluster-based fusion (GCR) is developed to handle the case of unknown intruder’s parameters. Simulation results show that the OCR performance is close to the Chair-Varshney rule. In fact, the latter benchmark can be reached by forming more clusters in the network without increasing the SN deployment intensity. Simulation results also show that the GCR performs very closely to the OCR when the number of clusters is large enough. The performance is further improved when the SN deployment intensity is increased.
Highlights
A wireless sensor network (WSN) consists of a large number of geographically distributed low-cost sensor nodes (SNs) forming a network via wireless links
The cluster heads (CHs) collects the local decisions of the SNs and sends the sum to the fusion center (FC)
We derived the optimal cluster-based fusion rule (OCR), which is the weighted average of the sums of local decisions at each cluster
Summary
A wireless sensor network (WSN) consists of a large number of geographically distributed low-cost sensor nodes (SNs) forming a network via wireless links. The SNs monitor the ROI to detect abnormal phenomena, which might take the form of temperature, electromagnetic, or acoustic disturbances Such physical signals are usually localized in space, i.e., the signal’s power attenuates with the distance between the source and the sensor. The effect of communication errors on distributed detection in multi-hop clustered WSN was considered in [23] where it was shown that the optimal fusion rule is a weighted order statistic filter. We adopt the network configuration in [8] in which a vast WSN is divided into geographical regions managed by CHs. we assume that within each CH, the SNs send a single bit, representing their local decision, to the CH due to bandwidth and power constraints. That the probability of detection in (6) depends on the target parameters P0 and x0 through (1)
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
