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MC2: Multimode User-Centric Design of Wireless Sensor Networks for Long-Term Monitoring.

Authors :
MING XIA
YABO DONG
WENYUAN XU
XIANGYANG LI
DONGMING LU
Source :
ACM Transactions on Sensor Networks; 2014, Vol. 10 Issue 3, p52-52:30, 30p
Publication Year :
2014

Abstract

Real-world, long-running wireless sensor networks (WSNs) require intense user intervention in the development, hardware testing, deployment, and maintenance stages. A majority of network design is network centric and focuses primarily on network performance, for example, efficient sensing and reliable data delivery. Although several tools have been developed to assist debugging and fault diagnosis, it is yet to systematically examine the underlying heavy burden that users face throughout the lifetime of WSNs. In this article, we propose a general Multimode user-CentriC (MC<superscript>2</superscript>) framework that can, with simple user inputs, adjust itself to assist user operation and thus reduce the users' burden at various stages. In particular, we have identified utilities that are essential at each stage and grouped them into modes. In each mode, only the corresponding utilities will be loaded, and modes can be easily switched using the customized MC<superscript>2</superscript> sensor platform. As such, we reduce the runtime interference between various utilities and simplify their development as well as their debugging. We validated our MC<superscript>2</superscript> software and the sensor platform in a long-lived microclimate monitoring system deployed at a wildland heritage site, Mogao Grottoes. In our current system, 241 sensor nodes have been deployed in 57 caves, and the network has been running for over five years. Our experimental validation shows that the MC<superscript>2</superscript> framework shortens the time for network deployment and maintenance, and makes network maintenance doable by field experts (in our case, historians). [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
15504859
Volume :
10
Issue :
3
Database :
Complementary Index
Journal :
ACM Transactions on Sensor Networks
Publication Type :
Academic Journal
Accession number :
96023561
Full Text :
https://doi.org/10.1145/2509856