2 Search Results for "Buchmann, Alejandro P."


Document
CluStRE: Streaming Graph Clustering with Multi-Stage Refinement

Authors: Adil Chhabra, Shai Dorian Peretz, and Christian Schulz

Published in: LIPIcs, Volume 338, 23rd International Symposium on Experimental Algorithms (SEA 2025)


Abstract
We present CluStRE, a novel streaming graph clustering algorithm that balances computational efficiency with high-quality clustering using multi-stage refinement. Unlike traditional in-memory clustering approaches, CluStRE processes graphs in a streaming setting, significantly reducing memory overhead while leveraging re-streaming and evolutionary heuristics to improve solution quality. Our method dynamically constructs a quotient graph, enabling modularity-based optimization while efficiently handling large-scale graphs. We introduce multiple configurations of CluStRE to provide trade-offs between speed, memory consumption, and clustering quality. Experimental evaluations demonstrate that CluStRE improves solution quality by 89.8%, operates 2.6× faster, and uses less than two-thirds of the memory required by the state-of-the-art streaming clustering algorithm on average. Moreover, our strongest mode enhances solution quality by up to 150% on average. With this, CluStRE achieves comparable solution quality to in-memory algorithms, i.e. over 96% of the quality of clustering approaches, including Louvain, effectively bridging the gap between streaming and traditional clustering methods.

Cite as

Adil Chhabra, Shai Dorian Peretz, and Christian Schulz. CluStRE: Streaming Graph Clustering with Multi-Stage Refinement. In 23rd International Symposium on Experimental Algorithms (SEA 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 338, pp. 11:1-11:20, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)


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@InProceedings{chhabra_et_al:LIPIcs.SEA.2025.11,
  author =	{Chhabra, Adil and Dorian Peretz, Shai and Schulz, Christian},
  title =	{{CluStRE: Streaming Graph Clustering with Multi-Stage Refinement}},
  booktitle =	{23rd International Symposium on Experimental Algorithms (SEA 2025)},
  pages =	{11:1--11:20},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-375-1},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{338},
  editor =	{Mutzel, Petra and Prezza, Nicola},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.SEA.2025.11},
  URN =		{urn:nbn:de:0030-drops-232493},
  doi =		{10.4230/LIPIcs.SEA.2025.11},
  annote =	{Keywords: graph clustering, community, streaming, online, memetic, evolutionary}
}
Document
Infrastructure for Smart Cities: The Killer Application for Event-Based Computing

Authors: Alejandro P. Buchmann

Published in: Dagstuhl Seminar Proceedings, Volume 7191, Event Processing (2007)


Abstract
Infrastructures for smart cities are considered a potential killer app for event-based computing. Event services are a crucial part of the infrastructure. The complexity of the event services is compounded by the richness of the events, the number of (mobile) sensors and devices, heterogeneity, requirements for seamless integration, unstable communication and interference, quality of service requirements, the need for context awareness and device orchestration and self-X properties.

Cite as

Alejandro P. Buchmann. Infrastructure for Smart Cities: The Killer Application for Event-Based Computing. In Event Processing. Dagstuhl Seminar Proceedings, Volume 7191, pp. 1-2, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2007)


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@InProceedings{buchmann:DagSemProc.07191.6,
  author =	{Buchmann, Alejandro P.},
  title =	{{Infrastructure for Smart Cities: The Killer Application for Event-Based Computing}},
  booktitle =	{Event Processing},
  pages =	{1--2},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2007},
  volume =	{7191},
  editor =	{Mani Chandy and Opher Etzion and Rainer von Ammon},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagSemProc.07191.6},
  URN =		{urn:nbn:de:0030-drops-11453},
  doi =		{10.4230/DagSemProc.07191.6},
  annote =	{Keywords: Events, event-based computing}
}
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