Wireless sensor networks: a survey
Computer Networks: The International Journal of Computer and Telecommunications Networking
Distributed deviation detection in sensor networks
ACM SIGMOD Record
Novelty detection: a review—part 1: statistical approaches
Signal Processing
TinyDB: an acquisitional query processing system for sensor networks
ACM Transactions on Database Systems (TODS) - Special Issue: SIGMOD/PODS 2003
In-Network Outlier Detection in Wireless Sensor Networks
ICDCS '06 Proceedings of the 26th IEEE International Conference on Distributed Computing Systems
OLINDDA: a cluster-based approach for detecting novelty and concept drift in data streams
Proceedings of the 2007 ACM symposium on Applied computing
Toward adaptive query processing in wireless sensor networks
Signal Processing
An adaptive in-network aggregation operator for query processing in wireless sensor networks
Journal of Systems and Software
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This paper presents an approach for adapting query processing in wireless sensor networks (WSN) based on the notions of quality of query services (QoQS) and novelty detection (ND). While the former concept captures the idea of possibly having different queries serviced in different ways by the same WSN, the second relates to a machine learning technique embedded in the WSN components that allows them to modify their query processing behavior in a dynamic fashion. This approach aims at the intelligent consumption of the limited resources available in these networks while still trying to deliver the data quality as expected by their client applications. In this context, four classes of QoQS (CoQoS) have been specified having in mind distinct levels of requirements in terms of accuracy and temporal behavior of the sensed data. Moreover, a new ND-based algorithm, named as AdaQuali (after ADAptive QUALIty control for query processing in WSN), is introduced in detail as a way to control the sensor node activities through the adjustment of their rates of data collection and transmission. For validation purposes, experiments with a simulation prototype have been conducted over real data, and the results achieved so far point to gains in terms of energy consumption reduction that vary from 1.73% to 42.99% for different CoQoS.