Predicting link quality using supervised learning in wireless sensor networks

Authors:
Yong Wang;Margaret Martonosi;Li-Shiuan Peh
Affiliations:
Princeton University, NJ;Princeton University, NJ;Princeton University, NJ
Venue:
ACM SIGMOBILE Mobile Computing and Communications Review
Year:
2007

Citing 29
Cited 7

C4.5: programs for machine learning

C4.5: programs for machine learning
Evidence-based static branch prediction using machine learning

ACM Transactions on Programming Languages and Systems (TOPLAS)
Mining time-changing data streams

Proceedings of the seventh ACM SIGKDD international conference on Knowledge discovery and data mining
Machine Learning

Machine Learning
Passive network tomography using Bayesian inference

Proceedings of the 2nd ACM SIGCOMM Workshop on Internet measurment
Bug isolation via remote program sampling

PLDI '03 Proceedings of the ACM SIGPLAN 2003 conference on Programming language design and implementation
A high-throughput path metric for multi-hop wireless routing

Proceedings of the 9th annual international conference on Mobile computing and networking
Taming the underlying challenges of reliable multihop routing in sensor networks

Proceedings of the 1st international conference on Embedded networked sensor systems
CODA: congestion detection and avoidance in sensor networks

Proceedings of the 1st international conference on Embedded networked sensor systems
Distributed regression: an efficient framework for modeling sensor network data

Proceedings of the 3rd international symposium on Information processing in sensor networks
AIDA: Adaptive application-independent data aggregation in wireless sensor networks

ACM Transactions on Embedded Computing Systems (TECS)
Link-level measurements from an 802.11b mesh network

Proceedings of the 2004 conference on Applications, technologies, architectures, and protocols for computer communications
Mitigating congestion in wireless sensor networks

SenSys '04 Proceedings of the 2nd international conference on Embedded networked sensor systems
TAG: a Tiny AGgregation service for Ad-Hoc sensor networks

OSDI '02 Proceedings of the 5th symposium on Operating systems design and implementationCopyright restrictions prevent ACM from being able to make the PDFs for this conference available for downloading
Temporal properties of low power wireless links: modeling and implications on multi-hop routing

Proceedings of the 6th ACM international symposium on Mobile ad hoc networking and computing
Failure Diagnosis Using Decision Trees

ICAC '04 Proceedings of the First International Conference on Autonomic Computing
Design and deployment of industrial sensor networks: experiences from a semiconductor plant and the north sea

Proceedings of the 3rd international conference on Embedded networked sensor systems
A unifying link abstraction for wireless sensor networks

Proceedings of the 3rd international conference on Embedded networked sensor systems
Siphon: overload traffic management using multi-radio virtual sinks in sensor networks

Proceedings of the 3rd international conference on Embedded networked sensor systems
Sympathy for the sensor network debugger

Proceedings of the 3rd international conference on Embedded networked sensor systems
Near-optimal sensor placements: maximizing information while minimizing communication cost

Proceedings of the 5th international conference on Information processing in sensor networks
Statistical model of lossy links in wireless sensor networks

IPSN '05 Proceedings of the 4th international symposium on Information processing in sensor networks
Telos: enabling ultra-low power wireless research

IPSN '05 Proceedings of the 4th international symposium on Information processing in sensor networks
MoteLab: a wireless sensor network testbed

IPSN '05 Proceedings of the 4th international symposium on Information processing in sensor networks
The Tenet architecture for tiered sensor networks

Proceedings of the 4th international conference on Embedded networked sensor systems
Data compression algorithms for energy-constrained devices in delay tolerant networks

Proceedings of the 4th international conference on Embedded networked sensor systems
Data Mining: Practical Machine Learning Tools and Techniques, Second Edition (Morgan Kaufmann Series in Data Management Systems)

Data Mining: Practical Machine Learning Tools and Techniques, Second Edition (Morgan Kaufmann Series in Data Management Systems)
Correlating instrumentation data to system states: a building block for automated diagnosis and control

OSDI'04 Proceedings of the 6th conference on Symposium on Opearting Systems Design & Implementation - Volume 6
A wireless sensor network for structural health monitoring: performance and experience

EmNets '05 Proceedings of the 2nd IEEE workshop on Embedded Networked Sensors

Ambiguous decision trees for mining concept-drifting data streams

Pattern Recognition Letters
Fast, accurate event classification on resource-lean embedded sensors

EWSN'11 Proceedings of the 8th European conference on Wireless sensor networks
A dynamic route change mechanism for mobile ad hoc networks

International Journal of Communication Networks and Distributed Systems
Radio link quality estimation in wireless sensor networks: A survey

ACM Transactions on Sensor Networks (TOSN)
An energy-efficient link quality monitoring scheme for wireless networks

Wireless Communications & Mobile Computing
Fast, Accurate Event Classification on Resource-Lean Embedded Sensors

ACM Transactions on Autonomous and Adaptive Systems (TAAS)
Data-driven link quality prediction using link features

ACM Transactions on Sensor Networks (TOSN)

Quantified Score

Hi-index	0.00

Visualization

Abstract

Routing protocols in sensor networks maintain information on neighbor states and potentially many other factors in order to make informed decisions. Challenges arise both in (a) performing accurate and adaptive information discovery and (b) processing/analyzing the gathered data to extract useful features and correlations. To address such challenges, this paper explores using supervised learning techniques to make informed decisions in the context of wireless sensor networks. We investigate the design space of both offline learning and online learning and use link quality estimation as a case study to evaluate their effectiveness. For this purpose, we present MetricMap, a metric-based collection routing protocol atop MintRoute that derives link quality using classifiers learned in the training phase, when the traditional ETX approach fails. The offline learning approach is evaluated on a 30-node sensor network testbed, and our results show that MetricMap can achieve up to 300% improvement over MintRoute in data delivery rate for high data rate situations, with no negative impact on other performance metrics. We also explore the possibility of using online learning in this paper.