NDLI: Reliable estimation of influence fields for classification and tracking in unreliable sensor networks

Content Provider	IEEE Xplore Digital Library
Author	Bapat, S. Kulathumani, V. Arora, A.
Copyright Year	2005
Description	Author affiliation: Dept. of Comput. Sci. & Eng., Ohio State Univ., Columbus, OH, USA (Bapat, S.; Kulathumani, V.; Arora, A.)
Abstract	The influence field of an object, a commonly exploited feature in science and engineering applications, is the region where the object is detectable by a given sensing modality. Being spatially distributed, this feature allows us to tradeoff nodal computation with network communication. By the same token, not only is its calculation subject to nodal failures and false detections, but also to channel fading and channel contention. In this paper, we study how to accurately and efficiently estimate the influence fields of objects in such an unreliable setting and how this reliable estimation of influence fields can be used to classify and track different types of objects. We derive, for node and network fault models, the necessary nodal density for reliably estimating the influence fields so that objects can be classified and tracked. We present four algorithmic techniques: temporal aggregation, probabilistic reporting, temporal segregation and spatial reconstruction, to deal with cases where the effective network density differs from this minimum. We provide corroboration of our analysis through field experiments with Mica2 sensor nodes wherever appropriate. Finally, we demonstrate how these results and techniques were applied to achieve reliable and efficient classification and tracking in a fielded system of 90 Mica2 sensor nodes that we called "A Line In The Sand'.
Sponsorship	IEEE Comput. Soc. TC-MARCH ACM SIGMICRO
Starting Page	60
Ending Page	69
File Size	376179
Page Count	10
File Format	PDF
ISBN	076952463X
DOI	10.1109/RELDIS.2005.26
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2005-10-26
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Intelligent networks Wireless sensor networks Shape Vehicles Object detection Sensor systems Sensor phenomena and characterization Computer network reliability Computer science Reliability engineering intrusion detection wireless sensor networks reliability faulttolerance
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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