Database Paper Browser

Back to papers

Declarative Data Serving: The Future of Machine Learning Inference on the Edge

Summary: Declarative data serving for edge ML inference: data flows across heterogeneous nodes governed by high-level constraints. Shows how heterogeneity and task-specific patterns complicate deployment, and outlines a database agenda for edge computing. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
12430
Venue
VLDB
Year
2021
Pagerank
4.3441378e-05
Overall Rank
9,415 | 34.51%
DOI
10.14778/3476249.3476302

Incoming Non-self Citations Over Time

Authors

Incoming Citations (Sorted by Pagerank)

Showing 2 of 2 citing papers.

Rank Citing Paper Year Venue Pagerank
10,325 KEN: An Execution Engine for Unstructured Database Systems 2026 VLDB 4.1945683e-05
10,853 Algorithmic Data Minimization for Machine Learning over Internet-of-Things Data Streams 2025 VLDB 4.1945683e-05
Previous Page 1 / 1 Next

Outgoing Citations (Sorted by Pagerank)

Showing 5 of 5 cited papers.

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

Previous Page 1 / 1 Next

Semantically Similar Papers