MétaCan
Menu
Back to cohort
Record W2021080064 · doi:10.1109/iccnc.2013.6504227

A queueing theoretic model for opportunistic network coding

2013· article· en· W2021080064 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venue2013 International Conference on Computing, Networking and Communications (ICNC) · 2013
Typearticle
Languageen
FieldComputer Science
TopicCooperative Communication and Network Coding
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsComputer scienceNetwork packetLinear network codingQueueing theoryComputer networkCoding (social sciences)Markov processMarkov chainMarkovian arrival processPoint processDiscrete time and continuous timeReal-time computingMathematics

Abstract

fetched live from OpenAlex

In this paper, we consider a scenario in which two users communicate via a single access point with two buffers using network coding. We focus on the particular situation when there are no packets in one of the buffers for network coding to proceed. In this case, there is a trade-off between the delay due to waiting for a coding opportunity and the increased efficiency of spectrum access due to network coding. In order to analyze this situation, we develop an analytical model for the system using a discrete time Markov chain (DTMC). The packet arrivals for any general arrival distribution are modeled as a discrete time Markovian arrival process (DMAP). We then find the age distribution of the waiting packets and hence determine the waiting-time which achieves the optimal trades-off between spectrum access efficiency and packet delay.

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.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.930
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0040.002
Research integrity0.0000.000
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 head0.135
GPT teacher head0.331
Teacher spread0.195 · 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