TiNA: a scheme for temporal coherency-aware in-network aggregation
Proceedings of the 3rd ACM international workshop on Data engineering for wireless and mobile access
Cleaning and querying noisy sensors
WSNA '03 Proceedings of the 2nd ACM international conference on Wireless sensor networks and applications
Mining distance-based outliers in near linear time with randomization and a simple pruning rule
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
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
Distributed fault detection of wireless sensor networks
DIWANS '06 Proceedings of the 2006 workshop on Dependability issues in wireless ad hoc networks and sensor networks
Online outlier detection in sensor data using non-parametric models
VLDB '06 Proceedings of the 32nd international conference on Very large data bases
Using sensorranks for in-network detection of faulty readings in wireless sensor networks
MobiDE '07 Proceedings of the 6th ACM international workshop on Data engineering for wireless and mobile access
Robust management of outliers in sensor network aggregate queries
MobiDE '07 Proceedings of the 6th ACM international workshop on Data engineering for wireless and mobile access
A Weighted Moving Average-based Approach for Cleaning Sensor Data
ICDCS '07 Proceedings of the 27th International Conference on Distributed Computing Systems
Outlier detection in sensor networks
Proceedings of the 8th ACM international symposium on Mobile ad hoc networking and computing
Another Outlier Bites the Dust: Computing Meaningful Aggregates in Sensor Networks
ICDE '09 Proceedings of the 2009 IEEE International Conference on Data Engineering
TACO: tunable approximate computation of outliers in wireless sensor networks
Proceedings of the 2010 ACM SIGMOD International Conference on Management of data
Random hyperplane projection using derived dimensions
Proceedings of the Ninth ACM International Workshop on Data Engineering for Wireless and Mobile Access
Declarative support for sensor data cleaning
PERVASIVE'06 Proceedings of the 4th international conference on Pervasive Computing
Outlier Detection Techniques for Wireless Sensor Networks: A Survey
IEEE Communications Surveys & Tutorials
SeTraStream: semantic-aware trajectory construction over streaming movement data
SSTD'11 Proceedings of the 12th international conference on Advances in spatial and temporal databases
Distributed similarity estimation using derived dimensions
The VLDB Journal — The International Journal on Very Large Data Bases
In-network approximate computation of outliers with quality guarantees
Information Systems
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Sensor nodes constitute inexpensive, disposable devices that are often scattered in harsh environments of interest so as to collect and communicate desired measurements of monitored quantities. Due to the commodity hardware used in the construction of sensor nodes, the readings of sensors are frequently tainted with outliers. Given the presence of outliers, decision making in sensor networks becomes much harder. In this work, we introduce PAO, a framework that can reliably and efficiently detect outliers in wireless sensor networks. PAO significantly reduces the bandwidth consumption during the outlier detection procedure, while being able to operate over multiple window types. Moreover, our framework possesses the ability to operate in either an exact mode, or an approximate one that further reduces the communication cost, thus covering a wide variety of application requirements.