Alice Marascu, Pascal Pompey, et al.
Big Data 2013
Dynamically detecting anomalies can be difficult in very large-scale infrastructure networks. The authors' approach addresses spatiotemporal anomaly detection in a smarter city context with large numbers of sensors deployed. They propose a scalable, hybrid Internet infrastructure for dynamically detecting potential anomalies in real time using stream processing. The infrastructure enables analytically inspecting and comparing anomalies globally using large-scale array processing. Deployed on a real pipe network topology of 1,891 nodes, this approach can effectively detect and characterize anomalies while minimizing the amount of data shared across the network. © 1997-2012 IEEE.
Alice Marascu, Pascal Pompey, et al.
Big Data 2013
J. Ray, V. Yadav, et al.
Geoscientific Model Development
Ernesto Arandia, Bradley Eck, et al.
WDSA 2014
Fearghal O'Donncha, Sean A. McKenna, et al.
OCEANS 2014