Flower: A Data Analytics Flow Elasticity Manager
Summary: Flower holistically manages elasticity across ingestion, analytics, and storage layers, addressing heterogeneous cloud resources and cross-layer workload dependencies. It combines optimization and control theory for workload analysis, resource-share optimization, dynamic provisioning, and unified monitoring. (summarized by gpt-5.6-luna on Jul 24 2026)
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Authors
- 1. Alireza Khoshkbarforoushha (Data61; The Australian National University)
- 2. Rajiv Ranjan (Newcastle University)
- 3. Qing Wang (The Australian National University)
- 4. Carsten Friedrich (Data61)
BibTeX Citation
@article{khoshkbarforoushha_vldb17,
title = {{Flower: A Data Analytics Flow Elasticity Manager}},
author = {Khoshkbarforoushha, Alireza and Ranjan, Rajiv and Wang, Qing and Friedrich, Carsten},
journal = {PVLDB},
series = {{VLDB} '17},
volume = {10},
number = {12},
pages = {1893--1896},
doi = {10.14778/3137765.3137804},
url = {https://doi.org/10.14778/3137765.3137804},
year = {2017}
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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 |
|---|---|---|---|---|
| 2,268 | PerfEnforce Demonstration: Data Analytics with Performance Guarantees | 2016 | SIGMOD | 8.7208889e-05 |
| 3,747 | TIRAMOLA: Elastic NoSQL Provisioning Through a Cloud Management Platform | 2012 | SIGMOD | 7.0552485e-05 |
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