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ORCIDDEBS 2022: Copenhagen, Denmark
- Yongluan Zhou, Panos K. Chrysanthis, Vincenzo Gulisano, Eleni Tzirita Zacharatou
:
16th ACM International Conference on Distributed and Event-based Systems, DEBS 2022, Copenhagen, Denmark, June 27 - 30, 2022. ACM 2022, ISBN 978-1-4503-9308-9
Keynotes
- Ioana Manolescu:
Teasing journalistic findings out of heterogeneous sources: a data/AI journey. 1 - Pat Helland:
I'm so glad I'm uncoordinated!: coordination is increasingly painful... what can be done? 2 - Frank McSherry:
Materialize: a platform for building scalable event based systems. 3 - Till Rohrmann:
Rethinking how distributed applications are built. 4 - Falaah Arif Khan:
It's funny because it's true: confronting scientific catechisms through comic books! 5
Panels
- Antoine Amarilli, Christophe Claramunt, Demetrios Zeinalipour-Yazti:
Climate change and computing: facts, perspectives and an open discussion. 6
Research track
- Evangelos Kolyvas, Spyros Voulgaris:
CougaR: fast and eclipse-resilient dissemination for blockchain networks. 7-18 - Vasileios Stavropoulos, Elias Alevizos, Nikos Giatrakos, Alexander Artikis:
Optimizing complex event forecasting. 19-30 - Steven Purtzel, Samira Akili, Matthias Weidlich:
Predicate-based push-pull communication for distributed CEP. 31-42 - Liuyang Ren, Paul A. S. Ward, Bernard Wong:
Toward reducing cross-shard transaction overhead in sharded blockchains. 43-54 - Artem Trofimov, Nikita Sokolov, Nikita Marshalkin, Igor Kuralenok, Boris Novikov:
Substream management in distributed streaming dataflows. 55-66 - Muhammed Tawfiqul Islam, Renata Borovica-Gajic, Shanika Karunasekera:
A multi-level caching architecture for stateful stream computation. 67-78 - Espen Volnes, Thomas Plagemann, Boris Koldehofe, Vera Goebel:
Travel light: state shedding for efficient operator migration. 79-84 - Roman Heinrich, Manisha Luthra, Harald Kornmayer, Carsten Binnig:
Zero-shot cost models for distributed stream processing. 85-90 - Bochra Boughzala, Christoph Gärtner, Boris Koldehofe:
Window-based parallel operator execution with in-network computing. 91-96 - Tilman Zuckmantel, Yongluan Zhou, Boris Düdder, Thomas T. Hildebrandt:
Event-based data-centric semantics for consistent data management in microservices. 97-102
Industry track
- Michail Tsenos, Aristotelis Peri, Vana Kalogeraki:
AMESoS: a scalable and elastic framework for latency sensitive streaming pipelines. 103-114 - Joffrey de Oliveira, Christophe Callé, Weiqin Xu, Philippe Calvez, Olivier Curé:
Knowledge graph stream processing at the edge. 115-125 - Vladimir Sladojevic, Sebastian Frischbier, Alexander Echler, Mario Paic, Alessandro Margara:
Deriving a realistic workload model to simulate high-volume financial data feeds for performance benchmarking. 126-131
Grand challenge track
- Sebastian Frischbier, Jawad Tahir, Christoph Doblander, Arne Hormann, Ruben Mayer, Hans-Arno Jacobsen:
Detecting trading trends in financial tick data: the DEBS 2022 grand challenge. 132-138 - Luca De Martini, Alessandro Margara, Gianpaolo Cugola:
Analysis of market data with Noir: DEBS grand challenge. 139-144 - Emmanouil Kritharakis, Shengyao Luo, Vivek Unnikrishnan, Karan Vombatkere:
Detecting trading trends in streaming financial data using Apache Flink. 145-150 - Quan Pham, Quang Nguyen, Ryte Richard, Shekhar Sharma, Xavier Ruiz:
Detecting technical trading patterns in financial data with Apache Flink: DEBS grand challenge 2022. 151-155 - Stefanos Kalogerakis, Antonis Papaioannou, Kostas Magoutis:
Efficient processing of high-volume tick data with Apache Flink for the DEBS 2022 grand challenge. 156-161 - Cecilia Calavaro, Gabriele Russo Russo, Valeria Cardellini:
Real-time analysis of market data leveraging Apache Flink. 162-165 - Kevin Li, Daniel Fernandez, David Klingler, Yuhan Gao, Jacob Rivera, Kia Teymourian:
A high-performance processing system for monitoring stock market data stream. 166-170 - Suyeon Wang, Jaekyeong Kim, Yoonsang Yang, Jinseong Hwang, Jungkyu Han, Sejin Chun:
Real-time stock market analytics for improving deployment and accessibility using PySpark and Docker. 171-175
Tutorials
- Alessandro Margara:
A unifying model for distributed data-intensive systems. 176-179
Demonstrations and Posters
- Pratyush Agnihotri, Boris Koldehofe, Carsten Binnig, Manisha Luthra:
PANDA: performance prediction for parallel and dynamic stream processing. 180-181 - Paschalis Mpeis, Athina Hadjichristodoulou, Jaime Bleye Vicario, Demetrios Zeinalipour-Yazti:
SMAS: a smart alert system for localization and first response to fires on ro-ro vessels. 182-185 - Timo Räth, Kai-Uwe Sattler:
StreamVizzard: an interactive and explorative stream processing editor. 186-189 - Yanghao Wang, Zhi Liu:
A sneak peek at RisingWave: a cloud-native streaming database. 190-193
Doctoral Symposium
- Timo Räth:
Interactive and explorative stream processing. 194-197
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