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Time-Critical Data Delivery in Wireless Sensor Networks

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSNConference contribution/Paperpeer-review

Published
Publication date06/2010
Host publicationProceedings of the 6th IEEE International Conference on Distributed Computing in Sensor Systems (DCOSS 2010)
EditorsRajmohan Rajaraman , Thomas Moscibroda , Adam Dunkels, Anna Scaglione
Place of PublicationBerlin
PublisherSpringer
Pages216-229
Number of pages14
ISBN (print)978-3-642-13650-4
<mark>Original language</mark>English
EventProceedings of the International Conference on Distributed Computing in Sensor Systems (DCOSS10), Santa Barbara, USA -
Duration: 1/01/1900 → …

Conference

ConferenceProceedings of the International Conference on Distributed Computing in Sensor Systems (DCOSS10), Santa Barbara, USA
Period1/01/00 → …

Conference

ConferenceProceedings of the International Conference on Distributed Computing in Sensor Systems (DCOSS10), Santa Barbara, USA
Period1/01/00 → …

Abstract

A number of wireless sensor network (WSN) applications demand timely data delivery. However, existing WSNs are designed to conserve energy and not to support timely data transmission. This paper shows how WSNs can be dimensioned, deployed and operated such that both reliable and timely data delivery is ensured while scarce energy is preserved. The presented solution employs a novel Medium Access Control (MAC) protocol that incorporates topology control mechanisms to ensure timely data delivery and reliability control mechanisms to deal with inherently fluctuating wireless links. An industrial process automation and control scenario at an oil refinery in Portugal is used to define protocol requirements. The paper details a TinyOS implementation of the protocol and its evaluation in a testbed. Under high traffic load, the protocol delivers 100% of data in time using a maximum node duty cycle as little as 2.48%. In an idle network a maximum node duty cycle of only 0.62% is achieved. This proposed protocol is thus an extremely energy efficient solution for time-critical data delivery.