Unreliable Multi Server Retrial Queueing System with Reneging and Diverse Outgoing Services
Bibliographic record
Abstract
This article explores a M/M/m unreliable retrial queue with reneging and diverse outgoing services.Incoming calls that arrive and discover all servers occupied join the orbit.The buffering incomings from the orbit retry their request after a while or leave the system without receiving service.When the orbit becomes empty, the idle server provides outgoing services.It is assumed that there are two categories of outgoing services.Due to unexpected circumstances, the server may breakdown.When a server undergoes breakdown, immediate repair process begins.Post-server breakdown, incoming calls go into orbit and retry service randomly, whereas the two variants of outgoing calls leave the system.The study utilizes a quasi-birth-death (QBD) process to analyse the stationary system size distribution.The steady state probabilities and the rate matrix are obtained through the matrix geometric method (MGM).Various performance metrics are evaluated for the proposed model.The study examines the impact of various system-based parameters on efficiency metrics with the help of numerical results.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".