Abstract
We examine the problem of discovering the set P of points in a given topology that constitutes a k-median set for that topology, while maintaining location privacy. That is, there exists a set U of points in a d-dimensional topology for which a k-median set must be found by some algorithm A, without disclosing the location of points in U to the executor of A. We define a privacy preserving data model for a coordinate system we call a "Topology Descriptor Grid", and show how it can be used to find the rectilinear 1-median of the system and a constant factor approximation for the Euclidean 1-median. We achieve a constant factor approximation for the rectilinear 2-median of a grid topology. Additionally we show upper and lower bounds for the k-center problem.
| Original language | English |
|---|---|
| Pages (from-to) | 3572-3601 |
| Number of pages | 30 |
| Journal | Algorithmica |
| Volume | 85 |
| Issue number | 12 |
| DOIs | |
| State | Published - 1 Dec 2023 |
Keywords
- Computational Geometry
- Geometric median
- Location privacy
- Privacy
ASJC Scopus subject areas
- General Computer Science
- Computer Science Applications
- Applied Mathematics
Fingerprint
Dive into the research topics of 'Finding Geometric Facilities with Location Privacy'. Together they form a unique fingerprint.Cite this
- APA
- Author
- BIBTEX
- Harvard
- Standard
- RIS
- Vancouver