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Record W1485325230 · doi:10.1002/0471643505.ch6

The M/G/1 Queue: Imbedded Markov Chains

2004· other· en· W1485325230 on OpenAlexaff
J.F. Hayes, Thimma V. J. Ganesh Babu

Bibliographic record

Venuenot available
Typeother
Languageen
FieldBusiness, Management and Accounting
TopicAdvanced Queuing Theory Analysis
Canadian institutionsConcordia University
Fundersnot available
KeywordsMarkov chainBurke's theoremQueueLaplace transformComputer scienceTopology (electrical circuits)MathematicsApplied mathematicsDiscrete mathematicsAlgorithmQueue management systemCombinatoricsComputer networkFork–join queueStatisticsMathematical analysis

Abstract

fetched live from OpenAlex

The M/G/1 queue is analyzed by means of a Markov chain imbedded at times of message departure from the system. As in the previous chapter the probability generating function is the mechanism for obtaining results on performance. The primary result is the Laplace transform of the probability density of message delay. This result leads directly to the Pollaczek-Khinchin formula for the average delay in M/G/1 queue. An analysis based on the concept of residual life provides an alternative derivation of this result. These same results are also derived for the case when message that arrive to an empty system receive different service. The next section provides a derivation of the mean and the Laplace transform for the duration of the busy period of the M/G/1 queue. In contrast, we next deal with the G/M/1 queue obtaining the steady state probabilities of the number of messages encountered by an arrival. The final topic treated is priority queue, both preemptive and non-pre-emptive. The results are applied to LANs with the ring topology.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.390
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0090.003

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 head0.222
Teacher spread0.215 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreOther

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

Citations0
Published2004
Admission routes1
Has abstractyes

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