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Record W2116970140 · doi:10.1109/twc.2009.080550

Distributed sender scheduling for multimedia transmission in wireless mobile peer-to-peer networks

2009· article· en· W2116970140 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

VenueIEEE Transactions on Wireless Communications · 2009
Typearticle
Languageen
FieldComputer Science
TopicPeer-to-Peer Network Technologies
Canadian institutionsUniversity of British ColumbiaCarleton University
Fundersnot available
KeywordsComputer scienceComputer networkScheduling (production processes)Wireless networkDistributed computingWirelessCommunication sourcePeer-to-peerTelecommunications

Abstract

fetched live from OpenAlex

Multi-source multimedia transmission is a popular architecture in wireless mobile peer-to-peer (P2P) networks. Most of previous work on wireless mobile P2P networks concentrates on the protocols and network structures, and consequently ignores the multiple senders scheduling problem. In this paper, we present a distributed algorithm for scheduling the multiple senders for multi-source transmission in wireless mobile P2P networks, which can maximize the data rate and minimize the power consumption. Specifically, we formulate the wireless mobile P2P network as a multi-armed bandit system. The optimal distributed sender scheduling policy can be found according to the Gittins indices of the senders. Extensive simulation examples illustrate the effectiveness of the proposed scheme. It is shown that the data rate and power consumption in the proposed scheme can be improved significantly compared to existing schemes.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.744
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.003
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0040.000
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 head0.028
GPT teacher head0.296
Teacher spread0.269 · 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