Adaptive data transformations for QaaS
Summary: Apply query-driven lightweight transformations (transcoding, chunking, sorting) via serverless functions to reshape semi-structured data for QaaS, offsetting lack of indexes to reduce latency and cost. Propose a cloud middleware that adaptively selects transformations per data/query under user-specified latency/cost budgets and empirically evaluates the trade-offs. (summarized by gpt-5-mini on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Dimitrios Koutsoukos (Apple; ETH Zurich)
- 2. Renato Marroquín (Oracle)
- 3. Ingo Müller (Google)
- 4. Ana Klimovic (ETH Zurich)
BibTeX Citation
@inproceedings{koutsoukos_cidr25,
address = {Amsterdam, Netherlands},
series = {{CIDR} '25},
title = {{Adaptive data transformations for QaaS}},
booktitle = {Proceedings of the {Conference} on {Innovative} {Data} {Systems} {Research}},
author = {Koutsoukos, Dimitrios and Marroquín, Renato and Müller, Ingo and Klimovic, Ana},
year = {2025}
}Incoming Citations (Sorted by Pagerank)
Showing 1 of 1 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 11,360 | UniClean: A Scalable Data Cleaning Solution for Mixed Errors based on Unified Cleaners and Optimized Cleaning Workflow | 2025 | VLDB | 4.9769913e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 19 of 19 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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