Accuracy-aware interference modeling and measurement in wireless sensor networks

Jun Huang, Shucheng Liu*, Guoliang Xing, Hongwei Zhang, Jianping Wang, Liusheng Huang

*Corresponding author for this work

Research output: Chapters, Conference Papers, Creative and Literary WorksRGC 32 - Refereed conference paper (with host publication)peer-review

29 Citations (Scopus)

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. © 2011 IEEE.
Original languageEnglish
Title of host publicationProceedings - 31st International Conference on Distributed Computing Systems
Subtitle of host publicationICDCS 2011
PublisherIEEE
Pages172-181
ISBN (Electronic)9780769543642
ISBN (Print)9781612843841
DOIs
Publication statusPublished - 2011
Event31st International Conference on Distributed Computing Systems, ICDCS 2011 - Minneapolis, MN, United States
Duration: 20 Jun 201124 Jul 2011

Publication series

Name
ISSN (Print)1063-6927
ISSN (Electronic)1063-6927

Conference

Conference31st International Conference on Distributed Computing Systems, ICDCS 2011
Country/TerritoryUnited States
CityMinneapolis, MN
Period20/06/1124/07/11

Bibliographical note

Full text of this publication does not contain sufficient affiliation information. With consent from the author(s) concerned, the Research Unit(s) information for this record is based on the existing academic department affiliation of the author(s).

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