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Record W4414037319 · doi:10.1109/jlt.2025.3606640

Availability-Aware Key Service With Dedicated Path Protection in Quantum Key Distribution Optical Networks

2025· article· en· W4414037319 on OpenAlexaff
Bowen Chen, Bing He, N. J. Zheng, Hong Chen, Weidong Shao, Limei Peng, Pin-Han Ho, Vimal Bhatia

Bibliographic record

VenueJournal of Lightwave Technology · 2025
Typearticle
Languageen
FieldComputer Science
TopicQuantum Information and Cryptography
Canadian institutionsUniversity of Waterloo
FundersMinistry of Science and ICT, South KoreaPriority Academic Program Development of Jiangsu Higher Education InstitutionsNational Research Foundation of KoreaNational Natural Science Foundation of China
KeywordsQuantum key distributionKey (lock)Computer scienceComputer networkKey distributionTelecommunicationsPath (computing)Electronic engineeringQuantumComputer securityPublic-key cryptographyEngineeringPhysicsQuantum mechanics

Abstract

fetched live from OpenAlex

Quantum key distribution (QKD)-based optical networks utilize quantum mechanics to secure communications by establishing secure, albeit expensive, quantum channels. A critical criterion for these QKD networks is to ensure network availability, which requires each service to adhere to a minimum unavailability constraint to maintain maximum network availability. This paper tackles the challenge of providing dedicated path protection for a select set of key services within QKD optical networks, adhering to specific unavailability constraints to ensure the gap between working and protection paths' unavailability remains within the allowable limit for each services. Considering the constraints of the limited timeslot resources and unavailability for the dedicated-path protection, we develop integer linear programming (ILP) models, to minimize the overall timeslot consumption in QKD optical networks. Additionally, we propose two novel algorithms for timeslot and availability management as minimum timeslot consumption (MTC) algorithm, and maximum availability (MA) algorithm to reduce the timeslot consumption. Simulations indicate that the ILP model based solution achieves the lowest timeslot consumption, however, it requires considerably more processing time compared to the proposed MTC and MA algorithms. Moreover, the MTC and MA algorithms outperform conventional dedicated-path protection (CDP) and fixed routing (FR) algorithms in reducing total timeslot consumption and improving average unavailability.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.877
Threshold uncertainty score0.459

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.004
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.007
GPT teacher head0.217
Teacher spread0.210 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2025
Admission routes1
Has abstractyes

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