The lecture is entitled “Big Data Analytics from the Rich Cloud to the Frugal Edge”
Over the past fifteen years, big data technologies played a crucial role in addressing challenging characteristics of data such as volume, variety and velocity. Such technologies were designed to work on computing clusters of (commodity) hardware. Yet, such clusters were centrally managed, assumed virtually infinite (rich) resources, and the data had to be moved to the cluster to get processed. This computing paradigm shift was further supported by the growing adoption of the cloud computing model. As of 2015, with the growing applications of Internet of Things, such as Smart-X applications, remote healthcare, etc., the data velocity and the stringent processing latency requirements have challenged big data technologies in directions beyond the principles these systems were designed for. Here, the terms fog computing and edge computing have emerged to further extend the notion of cloud computing. In essence, we need to process the data closer to where it is generated and avoid long trips to the cloud. Even more, this is not just due to business requirements but also to regulatory ones, e.g. GDPR. Processing data on the fog/edge has to respect the limited computing resources on these devices, data privacy, and the unstable nature of such computing networks. In his lecture, Professor Awad will discuss the challenges of conducting big data analytics across the hierarchy of the computing network (cloud/fog/edge). The lecture will cover the new challenges brought by extending the scope of processing and present a vision towards architectures to be realised over the next decade.
Ahmed Awad is a Professor of Big Data at the University of Tartu Institute of Computer Science since 2020. Awad’s interests are centred around the efficient management of data and their processing systems. Awad got his doctoral degree from Hasso Plattner Institute, Potsdam University, Germany, in 2010. Awad’s past experience is in data streams processing, complex event processing and application thereof in fields such as process mining, decentralised computation and machine learning on data streams. He has supervised eight master’s students and five doctoral students and published over 70 scientific articles. He is a member of the programme committee of several conferences and workshops.
All are welcome to attend!
This event is organised following the instructions by the Government of Estonia and the Estonian Health Board.
Before entering the assembly hall, participants of the lecture must present a valid health certificate to prove the person has been vaccinated or recovered from Covid-19. Make sure to have an ID document with you.
Please do not attend the event if you are ill or have felt ill or been in close contact with someone diagnosed with Covid-19 in the past 14 days.
There will be a live webcast of the lecture, which can be viewed on the university’s video portal www.uttv.ee