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Record W2162676381 · doi:10.1109/infcom.1995.515970

Multicast and self-routing in ATM radix trees and banyan networks

2002· article· en· W2162676381 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicInterconnection Networks and Systems
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsBanyanComputer scienceRouting (electronic design automation)Decoding methodsMulticastTree (set theory)Radix (gastropod)Computer networkMultistage interconnection networksBinary treeAlgorithmTheoretical computer scienceMathematicsCombinatorics

Abstract

fetched live from OpenAlex

Considers methods that perform all point-to-multipoint permutations in ATM radix tree and banyan networks. The authors investigate the relationship between the structure of the routing tab and the ease of performing multicasting. They first consider a simple explicit addressing scheme that requires (N-1)(log/sub 2/N+1) routing bits. They then present an addressing filtering scheme that requires N routing bits. Next they propose a new method, the vertex isolation addressing (VIA) scheme, which requires r(N-1)/(r-1) bits for radix-r tree networks. Thus for binary trees the routing tab i 2(N-1) bits long and as r approaches N the routing tab approaches N bits. The authors demonstrate that the "excess" bits in the VIA routing tab provide certain error detection capabilities. Encoding and decoding algorithms and hardware implementations for the VIA method are presented. Modified VIA schemes are then investigated for large tree networks. Finally the authors show that the VIA scheme and its modifications are applicable to banyan 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.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.982
Threshold uncertainty score0.297

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 science0.0000.000
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 head0.013
GPT teacher head0.201
Teacher spread0.188 · 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

Quick stats

Citations6
Published2002
Admission routes1
Has abstractyes

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