Reliability of geo-replicated cloud storage systems
Ilias Iliadis, Dmitry Sotnikov, et al.
PRDC 2014
As sensors are adopted in almost all fields of life, the Internet of Things (IoT) is triggering a massive influx of data. We need efficient and scalable methods to process this data to gain valuable insight and take timely action. Existing approaches which support both batch processing (suitable for analysis of large historical data sets) and event processing (suitable for real-time analysis) are complex. We propose the hut architecture, a simple but scalable architecture for ingesting and analyzing IoT data, which uses historical data analysis to provide context for real-time analysis. We implement our architecture using open source components optimized for Big Data applications and extend them, where needed. We demonstrate our solution on two real-world smart city use cases in transportation and energy management.
Ilias Iliadis, Dmitry Sotnikov, et al.
PRDC 2014
George Kousiouris, Adnan Akbar, et al.
Future Generation Computer Systems
Naama Parush, Dan Pelleg, et al.
ICAC 2009
Paula Ta-Shma, Guy Khazma, et al.
Big Data 2020