DocumentCode :
2396526
Title :
Accuracy-Aware Interference Modeling and Measurement in Wireless Sensor Networks
Author :
Huang, Jun ; Liu, Shucheng ; Xing, Guoliang ; Zhang, Hongwei ; Wang, Jianping ; Huang, Liusheng
Author_Institution :
Michigan State Univ., East Lansing, MI, USA
fYear :
2011
fDate :
20-24 June 2011
Firstpage :
172
Lastpage :
181
Abstract :
Wireless Sensor Networks (WSNs) are increasingly available for mission-critical applications such as emergency management and health care. To meet the stringent requirements on communication performance, it is crucial to understand the complex wireless interference among sensor nodes. Recent empirical studies suggest that the packet-level interference model, also referred to as the packet reception ratio (PRR) versus SINR model or PRR-SINR model, offers significantly improved realism than other simplistic models such as the disc model. However, as shown in our experimental results, the PRR-SINR model yields considerable spatial and temporal variations in reality, which poses a major challenge for accurate measurement at run time. This paper presents a novel accuracy-aware approach to interference modeling and measurement for WSNs. First, we propose a new regression-based PRR-SINR model and analytically characterize its accuracy based on statistics theory. Second, we develop a novel protocol called accuracy-aware interference measurement (AIM) for measuring the proposed PRR-SINR model with assured accuracy at run time. AIM also adopts new clock calibration and in-network aggregation techniques to reduce the overhead of interference measurement. Our extensive experiments on a 17-node testbed of TelosB motes show that AIM achieves high accuracy of PRR-SINR modeling with significantly lower overhead than state of the art approaches.
Keywords :
radiofrequency interference; wireless sensor networks; AIM; PRR-SINR modeling; WSN; accuracy-aware approach; accuracy-aware interference modeling; complex wireless interference; packet reception ratio; wireless sensor networks; Accuracy; Adaptation models; Analytical models; Interference; Signal to noise ratio; Time measurement; Wireless sensor networks;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Distributed Computing Systems (ICDCS), 2011 31st International Conference on
Conference_Location :
Minneapolis, MN
ISSN :
1063-6927
Print_ISBN :
978-1-61284-384-1
Electronic_ISBN :
1063-6927
Type :
conf
DOI :
10.1109/ICDCS.2011.47
Filename :
5961674
Link To Document :
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