Demo Data from VLDB 2026 / reviewers in the wild / expert
Tony X. Zhou
dblp:378/5933
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2025
0000-0002-8451-3385ORCID · reported
Domains — the database's venue-derived domains; a paper can count in several
Computer networks · 1 · 1 since 2021
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Computer architecture, parallel and distributed computing, and storage systems
1 paper |
Emerging computing paradigms · 67% Electronic design automation · 33% | |
| Computer networks
1 paper |
Network optimization and economics · 100% |
Topics — the 4 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Electronic design automation › physical design › timing optimization
delay optimization |
0.9 | 1 | 2025 | Entanglement Distribution Delay Optimization in Quantum Networks With Distillation · IEEE J. Sel. Areas Commun. 2025 |
Emerging computing paradigms › quantum computer architecture › quantum network
entanglement distribution |
0.9 | 1 | 2025 | Entanglement Distribution Delay Optimization in Quantum Networks With Distillation · IEEE J. Sel. Areas Commun. 2025 |
Emerging computing paradigms › quantum computer architecture
quantum network |
0.9 | 1 | 2025 | Entanglement Distribution Delay Optimization in Quantum Networks With Distillation · IEEE J. Sel. Areas Commun. 2025 |
Network optimization and economics
resource allocation |
0.3 | 1 | 2025 | Entanglement Distribution Delay Optimization in Quantum Networks With Distillation · IEEE J. Sel. Areas Commun. 2025 |
Methods — techniques the papers use, named apart from their topics
simulation · 1.7simulated annealing · 1.7analytical modeling · 1.7
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2025 | Entanglement Distribution Delay Optimization in Quantum Networks With DistillationabstractQuantum networks (QNs) enable secure distributed quantum computing and sensing over next-generation optical communication networks by distributing entangled states over optical channels. However, quantum switches (QSs) in such QNs, which perform entanglement distribution, have limited resources, e.g., single-photon sources (SPSs) and quantum memories, which are sensitive to noise and losses. Efficient QS resource allocation is needed to minimize entanglement distribution delay. This paper proposes a QS resource allocation framework that jointly optimizes the average entanglement distribution delay and entanglement distillation operations to improve end-to-end (e2e) fidelity and meet user-specific rate and fidelity requirements. The proposed framework accounts for realistic QN noise and imperfections, deriving analytical expressions for quantum memory decoherence noise and resulting e2e fidelity after distillation. It also considers practical deployment factors, allowing QSs to control 1) nitrogen-vacancy (NV) center SPS types based on their isotopic decomposition, and 2) nuclear spin regions based on coupling strength and distance from NV center’s electron spin. The QS resource allocation optimization problem is solved using a simulated annealing algorithm. Simulation results show that the proposed framework manages to satisfy all users rate and fidelity requirements, unlike existing distillation-agnostic, minimal distillation, and physics-agnostic frameworks which do not perform distillation, perform minimal distillation, and do not control the physics-based NV center characteristics, respectively. Furthermore, the proposed framework results in significant reductions in the average e2e entanglement distribution delay, along with enhancements in the average e2e fidelity compared to the aforementioned existing frameworks. Mahdi Chehimi, Kenneth Goodenough, Walid Saad 0001, Don Towsley, Tony X. Zhou |
IEEE J. Sel. Areas Commun. | 5 |