In general, my research focuses on distributed data stream algorithms and
their applications. Currently I am working on:
- Data stream algorithms for detecting exploit patterns from network flows
- Distributed algorithms for data aggregation and data mining in P2P and wireless sensor networks
Refereed Conference Publications
- "Finding Critical Thresholds for Defining Bursts" (pdf), Bibudh Lahiri, Fabian Moerchen and Ioannis Akrotirianakis, in the Proceedings of the 13th International Conference on Data Warehousing and Knowledge Discovery (DaWaK), 2011
- "Space-efficient Tracking of Persistent Items in a Massive Data Stream" (pdf), Bibudh Lahiri, Jaideep Chandrashekar and Srikanta Tirthapura, in the Proceedings of the 5th ACM International Conference on Distributed Event-Based Systems (DEBS), 2011
- "Finding Correlated Heavy-Hitters over Data Streams" (pdf), Bibudh Lahiri and Srikanta Tirthapura, in the Proceedings of the 28th IEEE International Performance Computing and Communications Conference (IPCCC), 2009 (slides in ppt)
- "Computing Frequent Elements using Gossip" (pdf), Bibudh Lahiri and Srikanta
Tirthapura, in the Proceedings of the 15th International Colloquium on
Structural Information and Communication Complexity (SIROCCO), 2008 (slides in
ppt)
Journal Papers
- "Computing Frequent Items in a Network using Gossip", Bibudh Lahiri and Srikanta Tirthapura, Journal of Parallel and Distributed Computing (JPDC) (pdf)
Book Chapters (invited)
- "Stream Sampling", Bibudh Lahiri and Srikanta Tirthapura, published in Encyclopedia of Database Systems, by Springer
Research Contest
- "A Generic Framework for Detecting Top-k Items from a Stream" (extended abstract), accepted for presentation in ACM Student Research Contest, held in Milwaukee, WI, March 2010 (poster, slides)