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An Experimental Study of ZigBee for Body Sensor Networks

  • José Augusto Afonso
  • Diogo Miguel Ferreira Taveira Gomes
  • Rui Miguel Costa Rodrigues
Conference paper

Abstract

We present an experimental performance evaluation of ZigBee networks in the context of data-intensive body sensor networks (BSNs). IEEE 802.15.4/ZigBee devices were mainly developed for use in wireless sensors network (WSN) applications; however, due to characteristics such as low power and small form factor, they are also being widely used in BSN applications, making it necessary to evaluate their suitability in this context. The delivery ratio and end-to-end delay were evaluated, under contention, for both star and tree topologies. The reliability of the ZigBee network in a star topology without hidden nodes was very good (delivery ratio close to 100 %), provided the acknowledgement mechanism was enabled. On the other hand, the performance in a tree topology was degraded due to router overload and the activation of the route maintenance protocol triggered by periods of high traffic load. The effect of the devices’ clock drift and hidden nodes on the reliability of the star network was modeled and validated through experimental tests. In these tests, the worst-case delivery ratio when the acknowledgment is used decreased to 90 % with two sensor nodes, while for the non-acknowledged mode the result was of 13 %. These results show that a mechanism for distributing the nodes’ traffic over the time is required to avoid BSN performance degradation caused by router overload, clock drift and hidden node issues.

Keywords

Body sensor networks Experimental study IEEE 802.15.4 Quality of service Wireless sensor networks ZigBee 

Notes

Acknowledgments

This work is funded by FEDER funds through “Programa Operacional Fatores de Competitividade—COMPETE” and by National Funds through FCT—Portuguese Foundation for Science and Technology in the scope of the Project FCOMP-01-0124-FEDER-022674 and Project PEst-OE/EEI/UI0319/2014.

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Copyright information

© Springer Science+Business Media Dordrecht 2014

Authors and Affiliations

  • José Augusto Afonso
    • 1
  • Diogo Miguel Ferreira Taveira Gomes
    • 1
  • Rui Miguel Costa Rodrigues
    • 1
  1. 1.Centro AlgoritmiUniversity of MinhoGuimarãesPortugal

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