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Radiation-aware data propagation in wireless sensor networks

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Published:24 October 2012Publication History

ABSTRACT

This research further investigates the recently introduced (in [4]) paradigm of radiation awareness in ambient environments with abundant heterogeneous wireless networking from a distributed computing perspective. We call radiation at a point of a wireless network the total amount of electromagnetic quantity the point is exposed to; our definition incorporates the effect of topology as well as the time domain and environment aspects. Even if the impact of radiation to human health remains largely unexplored and controversial, we believe it is worth trying to understand and control, in a way that does not decrease much the quality of service offered to users of the wireless network.

In particular, we here focus on the fundamental problem of efficient data propagation in wireless sensor networks, trying to keep latency low while maintaining at low levels the radiation cumulated by wireless transmissions. We first propose greedy and oblivious routing heuristics that are radiation aware. We then combine them with temporal back-off schemes that use local properties of the network (e.g. number of neighbours, distance from sink) in order to "spread" radiation in a spatio-temporal way. Our proposed radiation aware routing heuristics succeed to keep radiation levels low, while not increasing latency.

References

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  1. Radiation-aware data propagation in wireless sensor networks

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    • Published in

      cover image ACM Conferences
      MobiWac '12: Proceedings of the 10th ACM international symposium on Mobility management and wireless access
      October 2012
      176 pages
      ISBN:9781450316231
      DOI:10.1145/2386995
      • General Chair:
      • Jose Rolim,
      • Program Chairs:
      • Jun Luo,
      • Sotiris Nikoletseas

      Copyright © 2012 ACM

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      Association for Computing Machinery

      New York, NY, United States

      Publication History

      • Published: 24 October 2012

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      Overall Acceptance Rate83of272submissions,31%

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