PAQ: Time Series Forecasting for Approximate Query Answering in Sensor Networks

By Daniela Tulone, Samuel Madden. European Conference/Workshop on Wireless Sensor Networks, 2006

308 citations recorded by the source corpus.

Subfields: Building and Construction, Computer Networks and Communications, Signal Processing

View Paper: https://www.semanticscholar.org/paper/a9fd532ec7cfa6e488d09b94b55a3d27644cf40d

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Building and Construction

1. Mario Di Francesco
2. Andrea Passarella
3. Giuseppe Pio Anastasi
4. Marco Conti

In Computer Networks and Communications

1. Marco Conti
2. Mario Di Francesco
3. Andrea Passarella
4. Giuseppe Pio Anastasi
5. Hisashi Kashima
6. Zhili Sun
7. Eleonora Borgia
8. Robin I. M. Dunbar

In Signal Processing

1. Mario Di Francesco
2. Andrea Passarella
3. Giuseppe Pio Anastasi
4. Marco Conti

Citations in the corpus

• Distributed Multi-task Learning for Sensor Network (2017, background): “, [15], while they do not deal with collaborative learning among sensors.”
• Energy conservation in wireless sensor networks: A survey (2009, methodology): “PAQ [132] is based on a low-order AR model, with the aim of reducing the amount of computation to be performed by sensors.”