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Record W2807850458 · doi:10.17706/ijcce.2017.6.1.1-18

Using Modified Floyd-Warshall Algorithm to Implement SPB IEEE 802.1aq Protocol Simulator on NS-3

2017· article· en· W2807850458 on OpenAlexaff
Samuel A. Ajila, Yoonsoon Chang

Bibliographic record

VenueInternational Journal of Computer and Communication Engineering · 2017
Typearticle
Languageen
FieldComputer Science
TopicEnergy Efficient Wireless Sensor Networks
Canadian institutionsCarleton University
Fundersnot available
KeywordsComputer scienceProtocol (science)AlgorithmSimulationMedicine

Abstract

fetched live from OpenAlex

Ethernet has evolved to support various network topologies while maintaining its backward compatibility and simplicity.Virtualization of the provider's Ethernet network enables support for finegrained services for different users.Spanning Tree Protocol (STP) meets these properties but, still could benefit from improvements on utilization and convergence time.Shortest Path Bridging (SPB, IEEE 802.1aq) has been developed to overcome the shortcomings of STP.This paper presents the design and implementation of an SPB simulator for NS-3.The modified version of Floyd-Warshall algorithm is used to compute routes.Multicast and unicast communications are simulated in SPBM (SPB Mac-in-Mac) mode to show the simulator's capability.The results prove that the communication maintains the crucial property of SPB; congruency between multicast and unicast, and symmetry between forward and backward paths.The traffic route selected among candidate paths with the same cost is in accordance with the SPB standard.The contribution of this work is a powerful simulator that can be used to conduct experiments without the usual cost attached to the physical implementation.

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)0.001
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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.040
GPT teacher head0.338
Teacher spread0.299 · 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

Citations0
Published2017
Admission routes1
Has abstractyes

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