Minimizing Cost by Reducing Scaling Operations in Distributed Stream Processing
Summary: Reduces scaling frequency in elastic distributed stream processing by pre-filtering workload signals with signal-processing. Real-world testbed validation and break-even cost analysis show elasticity preserved with lower scaling overhead. (summarized by gpt-5-nano on Feb 09 2026)
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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 |
|---|---|---|---|---|
| 1,069 | Adaptive Stream Resource Management Using Kalman Filters | 2004 | SIGMOD | 0.00014285617 |
| 1,081 | Dhalion: Self-Regulating Stream Processing in Heron | 2017 | VLDB | 0.00014201838 |
| 1,120 | Albatross: Lightweight Elasticity in Shared Storage Databases for the Cloud using Live Data Migration | 2011 | VLDB | 0.00013846732 |
| 1,226 | Integrating Scale Out and Fault Tolerance in Stream Processing using Operator State Management | 2013 | SIGMOD | 0.00013168869 |
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