The video of the keynote talks and paper presentations is available here.

Workshop day: Tuesday April 20, 2021 (online event)

All times are CET

4:00-4:10pm Welcome by the workshop chairs

4:10-4:55pm KEYNOTE1 by Vincenzo Gulisano
Title: “Motivations and Challenges for Stream Processing in Edge Computing”
Abstract: The 2030 Agenda for Sustainable Development of the United Nations General Assembly defines 17 development goals to be met for a sustainable future. Goals such as Industry, Innovation and Infrastructure and Sustainable Cities and Communities depend on digital systems. As a matter of fact, billions of Euros are invested into digital transformation within the European Union, and many researchers are actively working to push state-of-the-art boundaries for techniques/tools able to extract value and insights from the large amounts of raw data sensed in digital systems. Edge computing aims at supporting such data-to-value transformation. In digital systems that traditionally rely on central data gathering, edge computing proposes to push the analysis towards the devices and data sources, thus leveraging the large cumulative computational power found in modern distributed systems. Some of the ideas promoted in edge computing are not new, though. Continuous and distributed data analysis paradigms such as stream processing have argued about the need for smart distributed analysis for basically 20 years. Starting from this observation, this talk covers a set of standing challenges for smart, distributed, and continuous stream processing in edge computing, with real-world examples and use-cases from smart grids and vehicular networks.

5:10-5:30pm Paper1: “Elastic Pulsar Functions for Distributed Stream Processing”
Authors: G.Russo Russo, A. Schiazza, V. Cardellini

5:35-5:50pm break

5:50-6:10pm Paper2: “An online approach to determine correlation between data streams”
Authors: D.K. Lal, U. Suman

6:15-7:00pm KEYNOTE2 by Marcos Assuncao (Teaser link)
Title: “Towards Elastic and Sustainable Data Stream Processing on Edge Infrastructures”
Abstract: Much of the data produced today is processed as it is generated by data stream processing systems. Although the cloud is often the target infrastructure for deploying data stream processing applications, resources located at the edges of the Internet have increasingly been used to offload some of the processing performed in the cloud and hence reduce the end-to-end latency when handling data events. In this work, I highlight some of the challenges in executing data stream processing applications on edge computing infrastructure and discuss directions for future research on making such applications more elastic and sustainable.

7:00-7:05pm Closing