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Epidemiology and Wireless Communication: Tight Analogy or Loose Metaphor?

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Bio-Inspired Computing and Communication (BIOWIRE 2007)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 5151))

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Abstract

The analogy between viral dynamics in humans and in computers is a detailed and useful one. At first glance, the extension to infectious disease epidemiology on human social networks and communication in wireless networks is also a compelling analogy. Mathematical epidemiology has a long history and seems to offer a biological inspiration for communication network design. In this paper, however, we argue that while epidemiology as a metaphor may hold insights into communication networks, the relationship is not concrete enough to permit us to adapt solutions from one domain to another. Our conclusion is that it is certain new mathematics and methodologies, rather than the results themselves, that are most likely to generalize well to communication systems.

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Author information

Authors and Affiliations

  1. Network Dynamics and Simulation Science Laboratory, VIrginia Bioinformatics Institute at Virginia Tech, USA

    Stephen Eubank, V. S. Anil Kumar & Madhav Marathe

Authors
  1. Stephen Eubank
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  2. V. S. Anil Kumar
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  3. Madhav Marathe
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Editor information

Editors and Affiliations

  1. The Computer Laboratory, University of Cambridge, William Gates Building, 15 JJ Thomson Avenue, CB3 0FD,, Cambridge, UK

    Pietro Liò

  2. Cambridge, UK

    Eiko Yoneki

  3. Cambridge University, UK

    Jon Crowcroft

  4. IBM TJ Watson Research Center, 704 Yorktown Heights, NY 10598, USA

    Dinesh C. Verma

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© 2008 Springer-Verlag Berlin Heidelberg

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Eubank, S., Anil Kumar, V.S., Marathe, M. (2008). Epidemiology and Wireless Communication: Tight Analogy or Loose Metaphor?. In: Liò, P., Yoneki, E., Crowcroft, J., Verma, D.C. (eds) Bio-Inspired Computing and Communication. BIOWIRE 2007. Lecture Notes in Computer Science, vol 5151. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-92191-2_9

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  • DOI: https://doi.org/10.1007/978-3-540-92191-2_9

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-92190-5

  • Online ISBN: 978-3-540-92191-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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