Project title: Performance optimizations of distributed stream processing platforms

Supervisor name: Dr. Saverio Niccolini, Dr. Mohamed Ahmed or someone with the same level of experience and/or expertise.

PhD enrolment: Y (UC3M)

Objectives: Given the dominant role in volume of multi-media content in today’s internet traffic and its expected continued growth, this work will look at how this traffic can be profiled and characterised accurately. The candidates will take part in developing new and innovative algorithms to help explain how users consume content, and predict content popularity growth patterns. The roles will combine both theoretical and practical approaches; candidates will work within a data driven role, and will help to develop highly scalable algorithms and processing platforms. This position will have a more practical system-oriented focus and the candidate will work in developing practical and scalable implementations of the analysis and modeling tools for stream mining content popularity evolution profiling.

Results: the candidate is expected to deliver scalable and accurate systems for mining large data sets with a focus on real-time analysis.

Dissemination: 1 to 2 publications per year to either conferences, magazine or journals

Planned secondment: Narus (during the second year for a period from 3 to 6 months).Narus is a Software company that provides real-time traffic intelligence and analytics tools which are required in this task to determine the required methodologies and components for data collection and analysis. Therefore, proper competence transfer between engineers at Narus with fellow researcher will be beneficial. Secondment might also be possible in Telefonica which is one of the major European operators.