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Efficient Scheduling of Data-Harvesting Trees

  • Conference paper
Algorithmic Aspects of Wireless Sensor Networks (ALGOSENSORS 2008)

Part of the book series: Lecture Notes in Computer Science ((LNCCN,volume 5389))

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Abstract

Many applications in sensor networks demand for energy and time optimal routing of data towards a sink. In this work we present mechanisms to set up energy and time efficient TDMA schedules for a given routing tree under very strict limitations: Nodes have only a constant size memory and must agree on a schedule using only a minimum of communication for set up: Each node is only allowed to send a single message to each of its neighbors.

We propose and analyze solutions in two different interference models. We show that, despite these tight restrictions, it is possible to compute energy optimal schedules which are almost time optimal and time optimal schedules which are almost energy optimal in the total interference model and we describe a 4-approximative algorithm in the k-local interference model.

We also show how to extend these mechanisms to settings with packet loss, while still guaranteeing bounds on energy consumption.

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References

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Author information

Authors and Affiliations

  1. Universität Karlsruhe (TH), Germany

    Bastian Katz, Steffen Mecke & Dorothea Wagner

Authors
  1. Bastian Katz
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  2. Steffen Mecke
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  3. Dorothea Wagner
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Editor information

Editors and Affiliations

  1. Department of Computer Science, Braunschweig University of Technology, 38106, Braunschweig, Germany

    Sándor P. Fekete

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© 2008 Springer-Verlag Berlin Heidelberg

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Katz, B., Mecke, S., Wagner, D. (2008). Efficient Scheduling of Data-Harvesting Trees. In: Fekete, S.P. (eds) Algorithmic Aspects of Wireless Sensor Networks. ALGOSENSORS 2008. Lecture Notes in Computer Science, vol 5389. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-92862-1_5

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  • DOI: https://doi.org/10.1007/978-3-540-92862-1_5

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-92861-4

  • Online ISBN: 978-3-540-92862-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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