About DEBS

Over the past decade, the ACM International Conference on Distributed and Event‐based Systems (DEBS) has become the premier venue for academia and industry to discuss cutting-edge research of event-based computing related to Big Data, AI/ML, IoT and Distributed Systems. The objectives of the ACM International Conference on Distributed and Event‐Based Systems (DEBS) are to provide a forum dedicated to the dissemination of original research, the discussion of practical insights, and the reporting of experiences relevant to distributed systems and event‐based computing. The conference aims at providing a forum for academia and industry to exchange ideas.

Download: DEBS 2019 Flyer

Scope

The DEBS conference covers topics in distributed and event-based computing. The scope of the conference includes systems dealing with collecting, detecting, processing and responding to events through distributed middleware and applications. Examples of application domains covered by the conference include the Internet of Things, sensor networks, social networking, finance, healthcare and logistics, computer and network security. Technologies discussed include real-time analytics, complex-event detection, reliability and resilience, energy management and green computing, data stream processing, big/fast data analysis, event processing for AI/ML, AI/ML for event processing, security and encryption in stream processing, embedded systems, and cloud, peer-to-peer, ubiquitous and mobile computing. Topics relevant to enterprise-level computing include enterprise application integration, real-time enterprises, Web services and support for enterprises to respond in timely fashion to changing situations.

Topics covered include, but are not limited to

  • Models, architectures and paradigms: Event-driven architectures, real-time analytics, complex event processing, event processing for AI/ML, event processing in big and fast data, data stream processing, security and encryption in stream processing, rule-based systems, in-network processing, logic-based event recognition, event correlation and pattern languages.
  • Systems and software: Distributed data processing, distributed programming, federated event-based systems, AI/ML for event processing, information-centric networking, software-defined networking, security, reliability and resilience, programmable hardware, energy management and green computing as well as cloud, fog, ubiquitous and mobile computing.
  • Applications: Use cases, requirements and applications of distributed and event-based systems in various domains including Internet-of-Things, cyber-physical systems, sensor networks, social networking, multimedia analytics, finance, healthcare and logistics, computer and network security, smart contracts and blockchains. Also, relevant topics span enterprise-level computing, including enterprise application integration, real-time enterprises, event-based business process management, and support for enterprises to respond in timely fashion to changing situations.
  • Structure

  • The Research Track presents original research contributions. Submissions will be evaluated by an experienced program committee consisting of eminent researchers from all over the world.
  • The Industry and Experience Reports Track is meant to report on innovative deployments of event-based systems. Contributions will be reviewed by researchers and industry practitioners working in distributed and event-based computing.
  • In the Tutorial Track recognized experts in the field will present their tutorials on relevant emerging areas of research.
  • In the Grand Challenge Track the committee will set out a grand challenge problem and then judge the most innovative approaches to its solution.
  • In the Poster and Demo Track authors report on work in progress and/or arrange to demonstrate interesting ideas and applications pertaining to distributed and event-based systems.
  • New at DEBS 2019: 1st DEBS Summer School on Machine Learning for Real-time Analytics
  • DEBS 2019 will conduct a one day-long summer school on Machine Learning for Real-time Analytics on June 24, 2019. The DEBS Summer School welcomes participation from graduate students, researchers and professionals who are interested in the topic of Machine Learning for Real-time Analytics and/or related fields. There will be keynotes by distinguished speakers.

  • Furthermore, following the tradition of the DEBS doctoral symposium, students can discuss and obtain feedback on their doctoral work from experienced researchers in the field of distributed and event-based computing.
  • Venue

    DEBS 2019 will be hosted by Technical University of Darmstadt in Hessen, Germany.

    Organizers

  • Boris Koldehofe, Technical University of Darmstadt
  • Guido Salvaneschi, Technical University of Darmstadt
  • Important Dates

    Abstract submission for research track February 19th March 8th, 2019
    Research and Industry paper submission February 26th March 8th, 2019
    Tutorial proposal submission March 22nd April 5, 2019
    Grand challenge solution submission April 7th April 22nd, 2019
    Author notification research and industry track April 9th April 19th, 2019
    Poster, demo & doctoral symposium submission April 22nd May 3rd, 2019
    Early registration May 31st, 2019

    Social Media

    Keynote

    Gustavo Alonso

    ETH Zurich, Switzerland

    Title: How Hardware Evolution is Driving Software Systems

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    Keynote

    Wolfgang Reisig

    Humboldt-Universität zu Berlin, Germany

    Title: Conceptual Modeling of Event-Based Systems

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    Keynote

    Tyler Akidau

    Google AI Research, USA

    Title: Open Problems in Stream Processing: A Call To Action

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    Keynote

    Karthik Ramasamy

    Streamlio Inc., USA

    Title: Unifying Messaging, Queuing, Streaming...

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    Keynote

    Donald Kossmann

    Microsoft Research, Redmond, USA

    Title: The Global AI Supercomputer                

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    Industry Talk

    Olivier Tardieu

    IBM Research, USA

    Title: Serverless Composition of Serverless Functions

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    Summer School Speaker

    Carsten Binnig

    TU Darmstadt, Germany

    Title: Towards Interactive Data Analytics        

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    Summer School Speaker

    Pedro Casas

    AIT GmbH, Austria

    Title: Continual Learning over Network Streaming Data...

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    Summer School Speaker

    Maja Rudolph

    Bosch Center for Artificial Intelligence

    Title: Time Series Modeling with Recurrent Neural Networks

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    Summer School Speaker

    Lars Dannecker

    SAP, Walldorf

    Title: Scalable Data Processing and Machine Learning...

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    Summer School Speaker

    Andreas Roth

    SAP, Walldorf

    Title: Scalable Data Processing and Machine Learning...

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    Sponsors