Direkt zum InhaltDirekt zur SucheDirekt zur Navigation
▼ Zielgruppen ▼

Humboldt-Universität zu Berlin - Mathematisch-Naturwissenschaftliche Fakultät - Process-Driven Architectures

Event Processing (VL/UE)

Prof. Dr. Matthias Weidlich

 

Content

Sensing of data is a major trend these days. The number of devices that are connected to the Internet and continuously emit events is growing drastically. Event processing systems are a technology that helps to make sense of these events, by filtering event data, transforming events, and matching event query patterns against a set of incoming event streams. Yet, the increasing volume, velocity, variety and distribution of event sources imposes challenges for the design and implementation of event processing systems. To cope with these requirements, various competing approaches have been proposed in the literature, each taking particular design decisions.

 

Structure

In the first part of the course, lectures and recitations will focus on the fundamental models and  algorithms of event processing systems. That includes common event models, languages for event processing, techniques to achieve robustness, and optimisations of event processing.

The second part of the course will be organised as a seminar. Each student will be asked to read a recent research paper on event processing (selection from a given list) and give a critical assessment of the approach presented in the paper in the form of a 45min presentation.

The course will be given in English. The first lecture will take place on Friday, 20th April, 2018.

 

Exam

There will be an oral exam at the end of the semester. To be eligible to take the exam, each student will be required to give a presentation (45min) on a research paper in the second part of the course. 

 

Exam dates:

  • Friday, August 3, 2018
  • Monday, August 6, 2018
  • Monday, August 13, 2018
  • Friday, October 12, 2018

Please register for one of the slots (30min, some time between 9am and 3pm) available at each of these dates with Mrs Riemer (Rud 25, room 4.402).

 

Credit Points

The course counts for 5 LP and is open for: Informatik, Master of Science (M.Sc.) Informatik, Master of Education (M.Ed.) Wirtschaftsinformatik, Master of Science (M.Sc.). The related area of specialisation is "Daten- und Wissensmanagement".

 
Students enrolled in the programme "Informatik, Diplom" may ask for an additional assignment task, which accounts for additional 3 LP.

 

Dates

VL Fr 13-15 RUD 26, Raum 1'307
UE Fr 15-17 RUD 26, Raum 1'307

 

 

 

 

Lecture Slides

 

Recitations

 

Presentation Slots

 

Date Topic and Presenters
   

June 29, 2018

1) Location-aware Pub/Sub (slides)
Christian Bell, Tim Sikatzki

7) TRex
Maria Walter, Gabriel Krause

   

July 06, 2018

9) Speculative Processing
Alexej Shabas, Jose Maguey

12) Fault Tolerance
Tobias Flaig, Leonie Reichert

16) Handshake Join
David Fradin, Sebastian Götte

17) Elastic Streaming
Benjamin Kolb, Murat Gökhan Yigit

   

July 13, 2018

4) Spatial Top-K Pub/Sub
Martin Bauer, Nicole Vieregg

10) Uncertain Events
Paul Jakob, Hagen Mohr

11) Imprecise CEP
Falk Meyer-Eschenbach, Alexander Senger

14) Semantic Optimisation
Lennart Grosser, Christoph Zyla

 

 

 

Presentation Topics

The talks are scheduled for 29.06.2018, 06.07.2018, and 13.07.2018.

 

1) Location-aware Pub/Sub

Long Guo, Dongxiang Zhang, Guoliang Li, Kian-Lee Tan, Zhifeng Bao: Location-Aware Pub/Sub System: When Continuous Moving Queries Meet Dynamic Event Streams. SIGMOD Conference 2015: 843-857 paper link

 

2) Overlay Mending in Pub/Sub

Chen Chen, Roman Vitenberg, Hans-Arno Jacobsen: OMen: overlay mending for topic-based publish/subscribe systems under churn. DEBS 2016: 105-116 paper link

 

3) Pub/Sub via Gossiping

Pooya Salehi, Christoph Doblander, Hans-Arno Jacobsen: Highly-available content-based publish/subscribe via gossiping. DEBS 2016: 93-104 paper link

 

4) Spatial Top-K Pub/Sub

Xiang Wang, Wenjie Zhang, Ying Zhang, Xuemin Lin, Zengfeng Huang: Top-k spatial-keyword publish/subscribe over sliding window. VLDB J. 26(3): 301-326 (2017) paper link

 

5) ZStream

Yuan Mei and Samuel Madden. ZStream: A cost-based query processor for adaptively detecting composite events. In Proceedings of the 2009 ACM SIGMOD International Conference on Management of data (SIGMOD ’09), pages 193–206, 2009. paper link

 

6) Secret

Nihal Dindar, Nesime Tatbul, Renee J. Miller, Laura M. Haas, and Irina Botan. Modeling the execution semantics of stream processing engines with secret. The VLDB Journal, 22(4):421–446, 2013. paper link

 

7) TRex

Gianpaolo Cugola and Alessandro Margara. Complex event processing with T-REX. J. Syst. Softw., 85(8):1709–1728, 2012. paper link

 

8) XML Streaming

Barzan Mozafari, Kai Zeng, Carlo Zaniolo: High-performance complex event processing over XML streams. SIGMOD Conference 2012: 253-264 paper link

 

9) Speculative Processing

Christopher Mutschler, Michael Philippsen: Adaptive Speculative Processing of Out-of-Order Event Streams. ACM Trans. Internet Techn. 14(1): 4:1-4:24 (2014) paper link

 

10) Uncertain Events

Segev Wasserkrug, Avigdor Gal, Opher Etzion, Yulia Turchin: Efficient Processing of Uncertain Events in Rule-Based Systems. IEEE Trans. Knowl. Data Eng. (TKDE) 24(1):45-58 (2012) paper link

 

11) Imprecise CEP

Haopeng Zhang, Yanlei Diao, Neil Immerman: Recognizing patterns in streams with imprecise timestamps. Inf. Syst. 38(8): 1187-1211 (2013) paper link

 

12) Fault Tolerance

Andre Martin, Thomas Knauth, Stephan Creutz, Diogo Becker de Brum, Stefan Weigert, Christof Fetzer, Andrey Brito: Low-Overhead Fault Tolerance for High-Throughput Data Processing Systems. ICDCS 2011: 689-699 paper link

 

13) Incremental Aggregation

K. Tangwongsan, M. Hirzel, S. Schneider, and K.-L. Wu. General Incremental Sliding-window Aggregation. Proc. VLDB Endow., 8(7):702–713, Feb. 2015 paper link

 

14) Semantic Optimisation

Luping Ding, Karen Works, Elke A. Rundensteiner: Semantic stream query optimization exploiting dynamic metadata. ICDE 2011:111-122 paper link

 

15) Pattern Sharing

Medhabi Ray, Chuan Lei, Elke A. Rundensteiner: Scalable Pattern Sharing on Event Streams. SIGMOD Conference 2016: 495-510 paper link

 

16) Handshake Join

Pratanu Roy, Jens Teubner, Rainer Gemulla: Low-Latency Handshake Join. PVLDB 7(9): 709-720 (2014) paper link

 

17) Elastic Streaming

Thomas Heinze, Mariam Zia, Robert Krahn, Zbigniew Jerzak, Christof Fetzer: An adaptive replication scheme for elastic data stream processing systems. DEBS 2015: 150-161 paper link

 

18) Saber

Alexandros Koliousis, Matthias Weidlich, Raul Castro Fernandez, Alexander L. Wolf, Paolo Costa, Peter R. Pietzuch: SABER: Window-Based Hybrid Stream Processing for Heterogeneous Architectures. SIGMOD Conference 2016: 555-569 paper link

 

See AGNES for further details: