Data Stream Processing for Packet-Level Analytics

Enabling Deep Analytics in Stream Processing Systems

Real-time applications often analyze data coming from sensor networks using relational and domain-specific operations such as signal processing and machine learning algorithms. To support such increasingly important scenarios, many data management systems integrate with numerical frameworks like R. Such solutions, however, incur significant performance penalties as relational engines and numeri...

High Level Synthesis for Packet Processing Pipelines

High Level Synthesis for Packet Processing Pipelines

Stream Analytics for Forecasting

The traditional approach of collecting, organising, storing, and analysing data is inadequate for applications where the reaction to events must be immediate. Filtering data streams prior to storage and analysis in order to reduce the volume of data is not efficient and degrades the information content that can be extracted. In contrast, new approaches, known as stream analytics, provide an abi...

Analytics on Big Fast Data Using Real Time Stream Data Processing Architecture

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Real-Time IoT Stream Processing and Large-scale Data Analytics for Smart City Applications