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Record W2172049743 · doi:10.1002/wcm.1159

Multichannel medium access control for ad hoc wireless networks

2011· article· en· W2172049743 on OpenAlexaff
Khaled H. Almotairi, Xuemin Shen

Bibliographic record

VenueWireless Communications and Mobile Computing · 2011
Typearticle
Languageen
FieldComputer Science
TopicMobile Ad Hoc Networks
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsComputer scienceComputer networkWireless ad hoc networkMultiple Access with Collision Avoidance for WirelessControl channelInterface (matter)Channel (broadcasting)ThroughputTransmission (telecommunications)Protocol (science)Synchronization (alternating current)Hidden node problemWireless networkWirelessNetwork interfaceData transmissionVehicular ad hoc networkWi-Fi arrayTelecommunicationsTelecommunications linkOperating system

Abstract

fetched live from OpenAlex

ABSTRACT In this paper, we study the multichannel exposed terminal problem in multihop wireless networks. We propose a multichannel medium access control (MAC) protocol, called multichannel MAC protocol with hopping reservation (MMAC‐HR), to resolve the multichannel exposed terminal problem. MMAC‐HR uses two radio interfaces; one interface is fixed over the control channel, and the other interface switches dynamically between data channels. The fixed interface supports broadcast information and reserves a data channel for any data transmission. The switchable interface, on other hand, is for data exchanges and follows independent slow hopping without requiring clock synchronization. In addition, the proposed protocol is a distributed one. By using the ns‐2 simulator, extensive simulations are performed to demonstrate that MMAC‐HR can enhance the network throughput and delay compared with existing multichannel MAC protocol. Copyright © 2011 John Wiley & Sons, Ltd.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.042
GPT teacher head0.287
Teacher spread0.246 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations26
Published2011
Admission routes1
Has abstractyes

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