Stochastic Consistency, and Scalable Pull-Based Caching for Erratic Data Stream Sources

Summary: Stochastic consistency for stateless, pull-based caches over erratic data streams (stocks, sensors) using Brownian motion to bound cached errors within user-defined tolerance and probability. A real-time pull-scheduler minimizes cache–source deviation under load, with experiments showing superiority to prior schemes. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID: 9215
Venue: VLDB
Year: 2004
Pagerank: 4.613363e-05
Overall Rank: 7,967 | 44.58%
DOI: -

Incoming Non-self Citations Over Time

Authors

1. Shanzhong Zhu
2. Chinya V. Ravishankar

Incoming Citations (Sorted by Pagerank)

Showing 2 of 2 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank
7,740	Client Assignment in Content Dissemination Networks for Dynamic Data	2005	VLDB	4.6632995e-05
12,096	Ratio Threshold Queries over Distributed Data Sources	2013	VLDB	4.1945683e-05

Outgoing Citations (Sorted by Pagerank)

Showing 0 of 0 cited papers.

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

Rank	Cited Paper	Year	Venue	Pagerank

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