Motivations and challenges for stream processing in edge computing
Paper in proceeding, 2021

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.

Data streaming; Edge Computing

Author

Vincenzo Massimiliano Gulisano

Chalmers, Computer Science and Engineering (Chalmers), Networks and Systems (Chalmers)

ICPE 2021 - Companion of the ACM/SPEC International Conference on Performance Engineering

17-18
9781450383318 (ISBN)

2021 ACM/SPEC International Conference on Performance Engineering, ICPE 2021
Virtual, Online, France,

Subject Categories

Other Computer and Information Science

History of Technology

Media Engineering

DOI

10.1145/3447545.3451899

More information

Latest update

5/12/2021