Modelling Periodic Data Dissemination in Wireless Sensor Networks

G Williamson; D Cellai; S Dobson; PA Nixon

doi:10.1109/EMS.2009.31

Modelling Periodic Data Dissemination in Wireless Sensor Networks

G Williamson, D Cellai, S Dobson, PA Nixon

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

12 Citations (Scopus)

Abstract

Epidemic-based communications, or 'gossiping', provides a robust and scalable method for maintaining a knowledge base in a sensor network faced with an unpredictable network environment. Since sensed information is often periodic in time, protocols should be able to manage multiple messages in an efficient way. We describe a mathematical model of gossiping dealing with multiple messages. We present simulation results that suggest the model can provide insights into the design and optimisation of sensor networks in the case of dissemination of periodically generated data. We show that it is possible to control data freshness without increasing overhead, and quantify the importance of topology in achieving timely dissemination.

Original language	English
Title of host publication	Unknown Host Publication
Editors	David Al-Dabass, Sokratis Katsikas
Publisher	IEEE Computer Society
Pages	499-504
Number of pages	6
ISBN (Print)	978-1-4244-5345-0
DOIs	https://doi.org/10.1109/EMS.2009.31
Publication status	Published (in print/issue) - 2009
Event	EMS 2009 UKSim Third European Modelling Symposium on Computer Modelling and Simulation - Athens, Greece Duration: 1 Jan 2009 → …

Conference

Conference	EMS 2009 UKSim Third European Modelling Symposium on Computer Modelling and Simulation
Period	1/01/09 → …

Keywords

n/a

Access to Document

10.1109/EMS.2009.31

Cite this

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abstract = "Epidemic-based communications, or 'gossiping', provides a robust and scalable method for maintaining a knowledge base in a sensor network faced with an unpredictable network environment. Since sensed information is often periodic in time, protocols should be able to manage multiple messages in an efficient way. We describe a mathematical model of gossiping dealing with multiple messages. We present simulation results that suggest the model can provide insights into the design and optimisation of sensor networks in the case of dissemination of periodically generated data. We show that it is possible to control data freshness without increasing overhead, and quantify the importance of topology in achieving timely dissemination.",

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AU - Cellai, D

AU - Dobson, S

AU - Nixon, PA

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N2 - Epidemic-based communications, or 'gossiping', provides a robust and scalable method for maintaining a knowledge base in a sensor network faced with an unpredictable network environment. Since sensed information is often periodic in time, protocols should be able to manage multiple messages in an efficient way. We describe a mathematical model of gossiping dealing with multiple messages. We present simulation results that suggest the model can provide insights into the design and optimisation of sensor networks in the case of dissemination of periodically generated data. We show that it is possible to control data freshness without increasing overhead, and quantify the importance of topology in achieving timely dissemination.

AB - Epidemic-based communications, or 'gossiping', provides a robust and scalable method for maintaining a knowledge base in a sensor network faced with an unpredictable network environment. Since sensed information is often periodic in time, protocols should be able to manage multiple messages in an efficient way. We describe a mathematical model of gossiping dealing with multiple messages. We present simulation results that suggest the model can provide insights into the design and optimisation of sensor networks in the case of dissemination of periodically generated data. We show that it is possible to control data freshness without increasing overhead, and quantify the importance of topology in achieving timely dissemination.

KW - n/a

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DO - 10.1109/EMS.2009.31

M3 - Conference contribution

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Y2 - 1 January 2009

ER -

Modelling Periodic Data Dissemination in Wireless Sensor Networks

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