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Record W2168993262 · doi:10.1109/lcn.2006.322142

The Internet Group Management Protocol with Access Control (IGMP-AC)

2006· article· en· W2168993262 on OpenAlexafffund
Salekul Islam, J. William Atwood

Bibliographic record

VenueConference on Local Computer Networks · 2006
Typearticle
Languageen
FieldEngineering
TopicIPv6, Mobility, Handover, Networks, Security
Canadian institutionsConcordia University
FundersNatural Sciences and Engineering Research Council of CanadaFonds Québécois de la Recherche sur la Nature et les TechnologiesConcordia University
KeywordsInternet Group Management ProtocolComputer scienceMulticastComputer networkIP multicastProtocol Independent MulticastXcastSource-specific multicastPragmatic General Multicast

Abstract

fetched live from OpenAlex

IP multicast is best known for its bandwidth conservation and lower resource utilization. The classical model of multicast makes it difficult to permit access only to authorized end users or paying customers. A scalable, distributed and secure architecture is needed where authorized end users can be authenticated before delivering any data or content. In (unsecure) multicast, an end user or host informs the multicast edge-router of its interest in receiving multicast traffic using the Internet group management protocol (IGMP). To carry the end user authentication data, we have extended the IGMPv3 protocol, and called our new version the Internet group management protocol with access control (IGMP-AC). New messages and reception states have been added to IGMPv3, and the AAA framework is used for end user authentication, authorization and accounting purposes. IGMP-AC is presented using state diagrams of the entities that are involved. The proposed protocol has been modeled in PROMELA, and has also been verified using SPIN

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)0.004
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 score0.005
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0010.002
Scholarly communication0.0030.003
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.002

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 head0.009
GPT teacher head0.218
Teacher spread0.209 · 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

Citations22
Published2006
Admission routes2
Has abstractyes

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