Learning from Deployment Experience

  • Elena Gaura
  • Michael Allen
  • Lewis Girod
  • Geoffrey Challen
  • James Brusey


Early developments in WSNs focused on minimizing the physical size and energy footprint of the nodes, and on exploring the opportunities and problems introduced by very large networks of low-cost nodes. In practice, however, deploying or testing systems at this scale has not been practical. At smaller scales, extreme resource constraints are often artificial. The evidence from surveying deployed applications suggests that in general, concerns about size, power, and large network scales are trumped by practical considerations relating to deployment such as packaging and logistics, and relating to what is commercially available for a reasonable price. In this chapter we introduce the characteristics of deployed WSN applications and discuss how they differ from lab-based experiments. We then distill some general design strategies from past deployment experiences, with particular reference to applications featured in Part II of the book. Next, we present a survey of platforms that are currently commercially available to use as starting points for WSN applications, and finally discuss the past and current market for WSN applications and products.


Sensor Network Sensor Node Wireless Sensor Network Deployment Experience Hype Cycle 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer Science+Business Media, LLC 2010

Authors and Affiliations

  • Elena Gaura
    • 1
  • Michael Allen
  • Lewis Girod
  • Geoffrey Challen
  • James Brusey
  1. 1.Cogent Computing Applied Research CentreCoventry UniversityCoventryUK

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