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Record W2137149451 · doi:10.1109/icn.2007.24

Architectural Analysis of Multicast Routing Protocols for Wireless Ad Hoc Networks

2007· article· en· W2137149451 on OpenAlexaff
Dewan Tanvir Ahmed, Shervin Shirmohammadi

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicMobile Ad Hoc Networks
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsComputer networkComputer scienceMulticastDistributed computingWireless ad hoc networkProtocol Independent MulticastOptimized Link State Routing ProtocolAdaptive quality of service multi-hop routingDistance Vector Multicast Routing ProtocolGeocastAd hoc wireless distribution serviceVehicular ad hoc networkXcastRouting protocolRouting (electronic design automation)WirelessTelecommunications

Abstract

fetched live from OpenAlex

Wireless ad hoc network is a dynamic network with the commitment of cooperative nodes. Multicasting is intended for group communication that supports the dissemination of information from a sender to all the receivers in a group. The difficulties of ad hoc networks are the scarcity of bandwidth, short lifetime due to power constraint, dynamic topology caused by nodes' mobility, etc. These problems put in force to design simple, robust and energy efficient multicast routing protocols for this environment. In this paper, we discuss the architecture of different multicast routing protocols, address their deployment issues and provide a guideline for the researchers in this field.

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)0.001
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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.875
Threshold uncertainty score0.564

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.021
GPT teacher head0.305
Teacher spread0.284 · 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 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

Citations9
Published2007
Admission routes1
Has abstractyes

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