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Record W2111286910 · doi:10.1109/his.2001.946708

New World Campus networking

2002· article· en· W2111286910 on OpenAlexaff
N.R. Figueira, Paul Bottorff, Huiwen Li

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicNetwork Traffic and Congestion Control
Canadian institutionsNortel (Canada)
Fundersnot available
KeywordsComputer networkComputer scienceClosetMulticastCampus networkGigabit EthernetLocal area networkVirtual LANServerData centerQuality of serviceEdge deviceEthernetFiber Distributed Data InterfaceNetworking hardwareMetropolitan area networkNetwork switchSimple (philosophy)EngineeringCloud computingOperating system

Abstract

fetched live from OpenAlex

The Old World Campus Network's rationale is based on the "locality principle", i.e., most network traffic is local and never leaves the edge of the network. Given this rationale, Closet, Building, and Campus Switches must provide layer 2 and 3 switching, management support, and QoS support. These requirements increase overall costs due to the complexity of operation and management of Closet and Building Switches. Today's client-server model of communication dominates in the campus environment, where most enterprise servers are located at the Data Center: this new model of communication justifies the New World Campus Network's (NWCN) rationale to eliminate needless levels of switching and to keep complex switches at the Data Center. This paper describes the NWCN proposal. In the NWCN, simple electronic 10 Gigabit Ethernet Multiplexors replace Closet Switches, optional DWDM multiplexors replace Building Switches, and a large Data Center Switch Complex performs all switching for the campus network. The NWCN provides a true multimedia network with simple and efficient central QoS handling, central management, and centralized multicast. Results of simulated experiments support the effectiveness of the NWCN proposal.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.071
Threshold uncertainty score0.236

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0040.003
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0710.031

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 head0.016
GPT teacher head0.198
Teacher spread0.182 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations0
Published2002
Admission routes1
Has abstractyes

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