NDLI: Temporal Adaptive Link Quality Prediction with Online Learning

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Convex Partitioning of Large-Scale Sensor Networks in Complex Fields: Algorithms and Applications

Occupancy Modeling and Prediction for Building Energy Management

A Cooperative MIMO Framework for Wireless Sensor Networks

Constructing Schedules for Time-Critical Data Delivery in Wireless Sensor Networks

Dynamic Networked Coverage of Time-Varying Environments in the Presence of Fading Communication Channels

Temporal Adaptive Link Quality Prediction with Online Learning

Combinatorial Filters: Sensor Beams, Obstacles, and Possible Paths

Efficient Solutions Framework for Optimal Multitask Resource Assignments for Data Fusion in Wireless Sensor Networks

Defending against Frequency-Based Attacks on Distributed Data Storage in Wireless Networks

Surface-Reflection-Based Communication and Localization in Underwater Sensor Networks

Connected Coverage in Wireless Networks with Directional Antennas

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Temporal Adaptive Link Quality Prediction with Online Learning

Content Provider	ACM Digital Library
Author	Cerpa, Alberto E. Liu, Tao
Copyright Year	2014
Abstract	Link quality estimation is a fundamental component of the low-power wireless network protocols and is essential for routing protocols in Wireless Sensor Networks (WSNs). However, accurate link quality estimation remains a challenging task due to the notoriously dynamic and unpredictable wireless environment. In this article we argue that, in addition to the estimation of current link quality, prediction of the future link quality is more important for the routing protocol to establish low-cost delivery paths. We propose to apply machine learning methods to predict the link quality in the near future to facilitate the utilization of intermediate links with frequent quality changes. Moreover, we show that, by using online learning methods, our adaptive link estimator (TALENT) adapts to network dynamics better than statically trained models without the need of a priori data collection for training the model before deployment. We implemented TALENT in TinyOS with Low-Power Listening (LPL) and conducted extensive experiments in three testbeds. Our experimental results show that the addition of TALENT increases the delivery efficiency 1.95 times on average compared with a 4B, state-of-the-art link quality estimator, as well as improves the end-to-end delivery rate when tested on three different wireless testbeds.
Starting Page	1
Ending Page	41
Page Count	41
File Format	PDF
ISSN	15504859
e-ISSN	15504867
DOI	10.1145/2594766
Volume Number	10
Issue Number	3
Journal	ACM Transactions on Sensor Networks (TOSN)
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2014-05-06
Publisher Place	New York
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Link quality estimation Link quality prediction
Content Type	Text
Resource Type	Article
Subject	Computer Networks and Communications

Sl.	Authority	Responsibilities	Communication Details
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
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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