Publications

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Conference Papers

  1. Ruben Mayer and Hans-Arno Jacobsen. 2021. “Hybrid Edge Partitioner: Partitioning Large Power-Law Graphs under Memory Constraints”. In Proceedings of the 2021 ACM SIGMOD International Conference on Management of Data (SIGMOD ‘21). Pages 1289–1302.

  2. Jeeta Ann Jacko, Ruben Mayer, and Hans-Arno Jacobsen. 2021. “Why Do My Blockchain Transactions Fail? A Study of Hyperledger Fabric”. In Proceedings of the 2021 ACM SIGMOD International Conference on Management of Data (SIGMOD ‘21). Pages 221–234.

  3. Pezhman Nasirifard, Ruben Mayer, and Hans-Arno Jacobsen. 2019. “FabricCRDT: A Conflict-Free Replicated Datatypes Approach to Permissioned Blockchains”. In Proceedings of the 20th ACM/IFIP International Middleware Conference (Middleware ‘19). Pages 110–122.

  4. Christian Mayer, Ruben Mayer, Sukanya Bhowmik, Lukas Epple, and Kurt Rothermel. 2018. “HYPE: Massive Hypergraph Partitioning with Neighborhood Expansion”. In Proceedings of the 2018 IEEE International Conference on Big Data (BigData ’18). Pages 458-467.

  5. Christian Mayer, Ruben Mayer, Muhammad Adnan Tariq, Heiko Geppert, Larissa Laich, Lukas Rieger, and Kurt Rothermel. 2018. “ADWISE: Adaptive Window-Based Streaming Edge Partitioning for High-Speed Graph Processing”. In Proceedings of the IEEE 38th International Conference on Distributed Computing Systems (ICDCS ‘18). Pages 685-695.

  6. Ruben Mayer, Ahmad Slo, Muhammad Adnan Tariq, Kurt Rothermel, Manuel Gräber, and Umakishore Ramachandran. 2017. “SPECTRE: Supporting Consumption Policies in Window-Based Parallel Complex Event Processing”. In Proceedings of the 18th ACM/IFIP/USENIX International Middleware Conference (Middleware ‘17). Pages 161-173.

  7. Thomas Bach, Muhammad Adnan Tariq, Ruben Mayer, and Kurt Rothermel. 2017. “Knowledge is at the Edge! How to Search in Distributed Machine Learning Models”. In Proceedings of OTM / CoopIS 2017 (OTM ‘17). Pages 410-428.

  8. Ruben Mayer, Leon Graser, Harshit Gupta, Enrique Saurez, and Umakishore Ramachandran. 2017. “EmuFog: Extensible and Scalable Emulation of Large-Scale Fog Computing Infrastructures”. In Proceedings of the 1st IEEE Fog World Congress (FWC ‘17). 6 pages.

  9. Ruben Mayer, Harshit Gupta, Enrique Saurez, and Umakishore Ramachandran. 2017. “FogStore: Toward a Distributed Data Store for Fog Computing”. In Proceedings of the 1st IEEE Fog World Congress (FWC ‘17). 6 pages.

  10. Ruben Mayer, Muhammad Adnan Tariq, and Kurt Rothermel. 2017. “Minimizing Communication Overhead in Window-Based Parallel Complex Event Processing”. In Proceedings of the 11th ACM International Conference on Distributed and Event-based Systems (DEBS ‘17). Pages 54-65.

  11. Ruben Mayer, Boris Koldehofe, and Kurt Rothermel. 2014. “Meeting Predictable Buffer Limits in the Parallel Execution of Event Processing Operators”. In Proceedings of the 2014 IEEE International Conference on Big Data (BigData ‘14). Pages 402-411.

  12. Boris Koldehofe, Ruben Mayer, Umakishore Ramachandran, Kurt Rothermel, and Marco Völz. 2013. “Rollback-recovery without checkpoints in distributed event processing systems”. In Proceedings of the 7th ACM International Conference on Distributed Event-Based Systems (DEBS ‘13). Pages 27-38.

Journal Papers

  1. Ruben Mayer and Hans-Arno Jacobsen. 2020. “Scalable Deep Learning on Distributed Infrastructures: Challenges, Techniques, and Tools”. ACM Computing Surveys 53, 1, Article 3 (May 2020), 37 pages.

  2. Henriette Röger and Ruben Mayer. 2019. “A Comprehensive Survey on Parallelization and Elasticity in Stream Processing”. ACM Computing Surveys 52, 2, Article 36 (May 2019), 37 pages.

  3. Christian Mayer, Muhammad Adnan Tariq, Ruben Mayer, and Kurt Rothermel. 2018. “GrapH: Traffic-Aware Graph Processing”. In IEEE Transactions on Parallel and Distributed Systems, vol. 29, no. 6, June 2018. Pages 1289-1302.

  4. Ruben Mayer, Boris Koldehofe, and Kurt Rothermel. 2015. “Predictable Low-Latency Event Detection with Parallel Complex Event Processing”. In IEEE Internet of Things Journal, vol. 2, no. 4, Aug. 2015. Pages 274-286.

Workshop Papers

  1. Thomas Kohler, Ruben Mayer, Frank Dürr, Marius Maaß, Sukanya Bhowmik, and Kurt Rothermel. 2018. “P4CEP: Towards In-Network Complex Event Processing”. In Proceedings of the 2018 Morning Workshop on In-Network Computing (NetCompute ‘18). ACM. Pages 33–38.

  2. Christian Mayer, Ruben Mayer, Jonas Grunert, Kurt Rothermel, and Muhammad Adnan Tariq. 2018. “Q-graph: Preserving Query Locality in Multi-Query Graph Processing”. In Proceedings of the 1st ACM SIGMOD Joint International Workshop on Graph Data Management Experiences & Systems (GRADES) and Network Data Analytics (NDA) (GRADES-NDA ‘18). Article 6. 10 Pages.

  3. Ruben Mayer, Christian Mayer, and Larissa Laich. 2017. “The TensorFlow Partitioning and Scheduling Problem: It’s the Critical Path!”. In Proceedings of the 1st Workshop on Distributed Infrastructures for Deep Learning (DIDL ‘17). ACM. Pages 1-6.

  4. Ruben Mayer, Harshit Gupta, Enrique Saurez, and Umakishore Ramachandran. 2017. “The Fog Makes Sense: Enabling Social Sensing Services with Limited Internet Connectivity”. In Proceedings of the 2nd International Workshop on Social Sensing, (SocialSens ‘17), ACM. Pages 61-66.

Others (Demos, Posters, etc.)

  1. Rinita Roy, Ruben Mayer, and Hans-Arno Jacobsen. 2021. “MDMS: Music Data Matching System for Query Variant Retrieval”. In Proceedings of the 29th ACM International Conference on Multimedia (MM ‘21). 3 Pages. To Appear.

  2. Jawad Tahir, Christoph Doblander, Ruben Mayer, Sebastian Frischbier, and Hans-Arno Jacobsen. 2021. “The DEBS 2021 Grand Challenge: Analyzing Environmental Impact of Worldwide Lockdowns”. In Proceedings of the 15th ACM International Conference on Distributed and Event-based Systems (DEBS ’21). Pages 136–141.

  3. Vincenzo Gulisano, Daniel Jorde, Ruben Mayer, Hannaneh Najdataei, and Dimitris Palyvos-Giannas. 2020. “The DEBS 2020 Grand Challenge”. In Proceedings of the 14th ACM International Conference on Distributed and Event-based Systems (DEBS ‘20). Pages 183–186.

  4. Christian Mayer, Ruben Mayer, and Majd Abdo. 2017. “StreamLearner: Distributed Incremental Machine Learning on Event Streams: Grand Challenge”. In Proceedings of the 11th ACM International Conference on Distributed and Event-based Systems (DEBS ‘17). Pages 298-303.

  5. Enrique Saurez, Harshit Gupta, Umakishore Ramachandran, and Ruben Mayer. 2017. “Fog Computing for Improving User Application Interaction and Context Awareness: Demo Abstract”. In Proceedings of the Second International Conference on Internet-of-Things Design and Implementation (IoTDI ‘17). Pages 281-282.

  6. Ruben Mayer, Christian Mayer, Muhammad Adnan Tariq, and Kurt Rothermel. 2016. “GraphCEP – Real-time Data Analytics Using Parallel Complex Event and Graph Processing”. In Proceedings of the 10th ACM International Conference on Distributed and Event-Based Systems (DEBS ‘16). Pages 309-316.

  7. Beate Ottenwälder, Ruben Mayer, and Boris Koldehofe. 2014. “Distributed Complex Event Processing for Mobile Large-Scale Video Applications”. In Proceedings of the Posters & Demos Session (Middleware Posters and Demos ‘14). Pages 5-6.

  8. Ruben Mayer. 2013. “Real-Time Distributed Complex Event Processing for Big Data Scenarios”. PhD Workshop at 7th ACM International Conference on Distributed Event-Based Systems (DEBS ‘13). 3 Pages.

Theses

  1. Ruben Mayer. 2018. “Window-based Data Parallelization in Complex Event Processing”. Dissertation, University of Stuttgart.

  2. Ruben Mayer. 2012. “Recovery of Event Streams in Complex Event Processing Systems”. Diploma Thesis, University of Stuttgart.