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Record W2155201381 · doi:10.1109/lcn.2004.14

Alleviating self-interference in MANETs

2004· article· en· W2155201381 on OpenAlexaff
Alex Varshavsky, Eyal de Lara

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicMobile Ad Hoc Networks
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsComputer networkComputer scienceNetwork packetNetwork topologyMobile ad hoc networkThroughputInterference (communication)Wireless ad hoc networkWirelessChannel (broadcasting)Telecommunications

Abstract

fetched live from OpenAlex

The interference range in multi-hop ad hoc networks (MANETs) is typically twice as large as the transmission range. This phenomenon causes packets of a multi-hop flow to interfere with each other as they are relayed over the multi-hop route. This interference, an instance of the notorious hidden terminal problem, is caused by simultaneous transmissions by down-stream nodes unaware of ongoing transmissions by up-stream nodes. DMAC (deferrable MAC) is a novel MAC protocol that alleviates the hidden terminal problem by deferring further transmissions until the previously transmitted packets travel far enough to avoid interference with the newly transmitted packets. For simple chain topologies, DMAC improves the throughput of CBR and TCP flows by up to 100% and 60%, respectively. For random mobile topologies with up to 40 simultaneous flows, DMAC improves the throughput of TCP flows by up to 30%.

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 categoriesnone
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 score0.856
Threshold uncertainty score0.304

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)0.0000.000

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 head0.011
GPT teacher head0.226
Teacher spread0.216 · 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
GenreMethods

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

Citations7
Published2004
Admission routes1
Has abstractyes

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