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Record W2033084785 · doi:10.1109/icoin.2008.4472779

New Multichannel MAC Protocol for Ad Hoc Networks

2008· article· en· W2033084785 on OpenAlexaff
T. Al-Meshhadany, Wessam Ajib

Bibliographic record

VenueThe International conference on information networking · 2008
Typearticle
Languageen
FieldComputer Science
TopicWireless Networks and Protocols
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsComputer networkComputer scienceWireless ad hoc networkAd hoc wireless distribution serviceMultiple Access with Collision Avoidance for WirelessReverse Address Resolution ProtocolOptimized Link State Routing ProtocolThroughputChannel access methodMedia access controlCode division multiple accessVehicular ad hoc networkTime division multiple accessWireless networkWirelessTelecommunicationsInternet protocol suite

Abstract

fetched live from OpenAlex

Since wireless ad hoc networks require a distributed multiple access protocol, the medium access control (MAC) layer can be seen as the bottleneck for the throughput in wireless 802.11-based ad hoc networks. In this paper, we develop a new MAC protocol for multichannel operation in wireless ad hoc networks. The proposed protocol is based on the code division multiple access (CDMA) technique where each spreading code represents one channel. However, the proposed MAC protocol is not limited to CDMA systems. It can be applicable within frequency division multiple access (FDMA) systems (with one radio transceiver) or multi radio systems. We show through computer simulations that our proposition of multichannel MAC protocol significantly improves the communication performance in wireless ad hoc networks.

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)0.002
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: Empirical · Consensus signal: none
Teacher disagreement score0.005
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0020.004
Open science0.0030.002
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0050.003

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 head0.093
GPT teacher head0.323
Teacher spread0.231 · 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
GenreEmpirical

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
Published2008
Admission routes1
Has abstractyes

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