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Series in Distributed Computing
edited by Roger Wattenhofer
Vol. 12

Nicolas Burri

Ultra-Low Power Sensor Networks:
Development Tools, Design, and
Implementation

1^st edition/1. Aufl. 2011, 144 pages/Seiten, € 64,00.
ISBN 978-3-86628-379-4

Wireless Sensor Networks (WSN) are a powerful tool for the surveillance of environmental conditions, natural habitats, or industrial machinery. All these applications require a long, independent operation of the network without human intervention. The lifetime of a network is limited by the restricted energy resources of the individual deployed sensor nodes. To maximize network lifetime it is therefore essential to minimize the power consumption of all nodes. To achieve energy-efficiency sensor nodes have to be kept in a sleep state in which they are neither able to execute computational tasks nor to communicate among themselves.

In this thesis we consider the design and implementation of energy-efficient communication protocols and applications for sensor networks. The thesis is organized in two orthogonal parts. The first part is dedicated to the Dozer project. Dozer is a communication system designed and optimized for applications in the domain of environmental monitoring. At a sample rate of one reading per two minutes, sensor nodes achieve a lifetime of up to ten years. This makes Dozer the most energy efficient system for applications with continuous, low data rates.

The second part of this thesis discusses development tools for sensor networks. With an application providing control and monitoring functionality and an integrated development environment on Eclipse-basis we provide TinyOS developers with tools to design, implement, and test their protocols more efficiently.

About the author:

Nicolas Burri received his M.Sc. degree in computer science (Dipl. Informatik-Ing.) from ETH Zurich, Switzerland in 2004. In the same year he joined the Distributed Computing Group of Professor Roger Wattenhofer at ETH Zurich as a Ph.D. student and research assistant. In 2010 he earned his Ph.D. degree for his work on energy efficient wireless sensor networks.

Keywords: wireless sensor networks, energy-efficiency, communication stack, data aggregation, development tools

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