Theory of Data Stream Computing: Where to Go

Summary: Reframes data-management theory for massive, high-rate streams that defy full capture, storage, or communication, advocating principled "work-with-less" algorithms. Surveys advances in stream algorithms, compressed sensing and DSMS and pinpoints open research challenges across computation, communication and storage. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID: 1553
Venue: PODS
Year: 2011
Pagerank: -
Overall Rank: 13,483 | 6.21%
DOI: -

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Authors

1. S. Muthukrishnan

Incoming Citations (Sorted by Pagerank)

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Rank	Citing Paper	Year	Venue	Pagerank

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Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank	Cited Paper	Year	Venue	Pagerank
2,894	Pan-private Algorithms Via Statistics on Sketches	2011	PODS	7.9474698e-05

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