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Sensor Network Calculus - A Framework for Worst Case Analysis.

Research output: Contribution in Book/Report/ProceedingsPaper

Published

Publication date30/06/2005
Host publicationDistributed Computing in Sensor Systems: First IEEE International Conference, DCOSS 2005, Marina del Rey, CA, USA, June 30 – July 1, 2005. Proceedings
EditorsViktor K. Prasanna, Sitharama S. Iyengar, Paul G. Spirakis, Matt Welsh
Place of publicationBerlin
PublisherSpringer Verlag
Pages141-154
Number of pages14
ISBN (Electronic)978-3-540-31671-8
ISBN (Print)978-3-540-26422-4
Original languageEnglish

Conference

ConferenceInternational Conference on Distributed Computing in Sensor Systems (DCOSS 2005)
Period1/01/00 → …

Publication series

NameLecture Notes in Computer Science
PublisherSpringer
Volume3560
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

ConferenceInternational Conference on Distributed Computing in Sensor Systems (DCOSS 2005)
Period1/01/00 → …

Abstract

To our knowledge, at the time of writing no methodology exists to dimension a sensor network so that a worst case traffic scenario can be definitely supported. In this paper, the well known network calculus is tailored so that it can be used as a tool for worst case traffic analysis in sensor networks. To illustrate the usage of the resulting sensor network calculus, typical example scenarios are analyzed by this new methodology. Sensor network calculus provides the ability to derive deterministic statements about supportable operation modes of sensor networks and the design of sensor nodes.

Bibliographic note

DCOSS is a well known conference on sensor networks which shares PC membership with the leading ACM SenSys and EWSN conferences. The paper describes a methodology that can be used to dimension a sensor network so that worst case traffic scenarios can be definitely supported. The well known network calculus is tailored for use as a tool for worst case traffic analysis in sensor networks. This is the first work that provides a dimensioning tool for sensor networks, and significant for deployment of sensor networks in critical application environments (e.g. traffic control, medical applications or production control) where it must be guaranteed that the required traffic patterns can be supported.