WANalytics: Analytics for a Geo-Distributed Data-Intensive World
Summary: WABD: running DAG analytics over geo-distributed data; centralizing raw data infeasible due to WAN cost, bandwidth limits, and data‑sovereignty. WANalytics pushes computation to edge DCs, optimizes DAG execution and selective replication; prototype yields 257× WAN reduction. (summarized by gpt-5-mini on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Ashish Vulimiri (University of Illinois Urbana-Champaign)
- 2. Carlo Curino (Microsoft)
- 3. Brighten Godfrey (University of Illinois Urbana-Champaign)
- 4. Konstantinos Karanasos (Microsoft)
- 5. George Varghese (Microsoft)
BibTeX Citation
@inproceedings{vulimiri_cidr15,
address = {Amsterdam, Netherlands},
series = {{CIDR} '15},
title = {{WANalytics: Analytics for a Geo-Distributed Data-Intensive World}},
booktitle = {Proceedings of the {Conference} on {Innovative} {Data} {Systems} {Research}},
author = {Vulimiri, Ashish and Curino, Carlo and Godfrey, Brighten and Karanasos, Konstantinos and Varghese, George},
year = {2015}
}
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