A line in the sand: a wireless sensor network for target detection, classification, and tracking

  • Authors:

  • A. Arora;P. Dutta;S. Bapat;V. Kulathumani;H. Zhang;V. Naik;V. Mittal;H. Cao;M. Demirbas;M. Gouda;Y. Choi;T. Herman;S. Kulkarni;U. Arumugam;M. Nesterenko;A. Vora;M. Miyashita

  • Affiliations:

  • Department of Computer Science and Engineering, The Ohio State University, Columbus, OH;Department of Computer Science and Engineering, The Ohio State University, Columbus, OH;Department of Computer Science and Engineering, The Ohio State University, Columbus, OH;Department of Computer Science and Engineering, The Ohio State University, Columbus, OH;Department of Computer Science and Engineering, The Ohio State University, Columbus, OH;Department of Computer Science and Engineering, The Ohio State University, Columbus, OH;Department of Computer Science and Engineering, The Ohio State University, Columbus, OH;Department of Computer Science and Engineering, The Ohio State University, Columbus, OH;Department of Computer Science and Engineering, The Ohio State University, Columbus, OH;Department of Computer Sciences, The University of Texas at Austin, Austin, TX;Department of Computer Sciences, The University of Texas at Austin, Austin, TX;Department of Computer Science, University of Iowa, Iowa City, IA;Department of Computer Science and Engineering, Michigan State University, East Lansing, MI;Department of Computer Science and Engineering, Michigan State University, East Lansing, MI;Department of Computer Science, Kent State University, Kent, OH;Department of Computer Science, Kent State University, Kent, OH;Department of Computer Science, Kent State University, Kent, OH

  • Venue:
  • Computer Networks: The International Journal of Computer and Telecommunications Networking - Special issue: Military communications systems and technologies
  • Year:
  • 2004

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Abstract

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.