A line in the sand: a wireless sensor network for target detection, classification, and tracking
Cited 260 times inCited 397 times in
- A line in the sand: a wireless sensor network for target detection, classification, and tracking
- Arora, A; Dutta, P; Bapat, S; Kulathumani, V; Zhang, H; Naik, V; Mittal, V; Cao, H; Demirbas, M; Gouda, M; Choi, Young-Ri; Herman, T; Kulkarni, S; Arumugam, U; Nesterenko, M; Vora, A; Miyashita, M
- Reliability; Stabilization; Smart dust; Target classification and tracking; Wireless sensor networks
- Issue Date
- ELSEVIER SCIENCE BV
- COMPUTER NETWORKS, v.46, no.5, pp.605 - 634
- Intrusion detection is a surveillance problem of practical import that is well suited to wireless sensor networks. In this paper, we study the application of sensor networks to the intrusion detection problem and the related problems of classifying and tracking targets. Our approach is based on a dense, distributed, wireless network of multi-modal resource-poor sensors combined into loosely coherent sensor arrays that perform in situ detection, estimation, compression, and exfiltration. We ground our study in the context of a security scenario called "A Line in the Sand" and accordingly define the target, system, environment, and fault models. Based on the performance requirements of the scenario and the sensing, communication, energy, and computation ability of the sensor network, we explore the design space of sensors, signal processing algorithms, communications, networking, and middleware services. We introduce the influence field, which can be estimated from a network of binary sensors, as the basis for a novel classifier. A contribution of our work is that we do not assume a reliable network; on the contrary, we quantitatively analyze the effects of network unreliability on application performance. Our work includes multiple experimental deployments of over 90 sensor nodes at MacDill Air Force Base in Tampa, FL, as well as other field experiments of comparable scale. Based on these experiences, we identify a set of key lessons and articulate a few of the challenges facing extreme scaling to tens or hundreds of thousands of sensor nodes.
- ; Go to Link
- Appears in Collections:
- EE_Journal Papers
- Files in This Item:
can give you direct access to the published full text of this article. (UNISTARs only)
Show full item record
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.