Big Data Processing

In the area of Big Data Processing, the focus of the DS group is on the design, implementation, analysis, and benchmarking big-data processing systems. Specific research topics are:

  • Designing and analyzing big-data processing systems

We have designed and analyzed of the BTWorld MapReduce-based workflow for analyzing monitoring data of the world-wide BitTorrent P2P system. With this work, we won the SCALE challenge at the CCGrid 2014 conference:

Bogdan Ghit, Mihai Capota, Tim Hegeman, Jan Hidders, Dick Epema, and Alexandru Iosup, "V for Vicissitude: The Challenge of Scaling Complex Big Data Workflows," CCGrid 2014.

  • Large-scale graph processing

 We are in the process of designing and implementing the Graphalytics graph processing benchmarking in collaboration with Intel Labs and Oracle.

  • Large-scale privacy-preserving video distribution

 Here is a video explaining our research.

Selected Publications on Big Data Processing

Please note: This page contains links to PostScript files of articles that may be covered by copyright. You may browse the articles at your convenience. (In the same spirit as you may read a journal or a proceeding article in a public library). Retrieving, copying, or distributing these files, however, may violate the copyright protection law. We recommend that the user abides international law in accessing this article list.

  • Y. Zhao, C. Lofi and C. Hauff (2017). Scalable Mind-Wandering Detection for MOOCs: A Webcam-Based Approach. In European Conf. on Technology Enhanced Learning (EC-TEL), Tallinn, Estonia. [ Bibtex ]
  • S. Mesbah, K. Fragkeskos, C. Lofi, A. Bozzon, G-J. Houben (2017). Facet Embeddings for Explorative Analytics in Digital Libraries. In Int. Conf. on Theory and Practice of Digital Libraries (TPDL), Thessaloniki, Greece,. [ Bibtex ]
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