MétaCan
Menu
Back to cohort
Record W2062839275 · doi:10.1117/12.570252

A framework for MPLS path setup in unidirectional multicast shared trees

2004· article· en· W2062839275 on OpenAlexaff
Ashraf Matrawy, Chung–Horng Lung, Ioannis Lambadaris

Bibliographic record

VenueProceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2004
Typearticle
Languageen
FieldComputer Science
TopicNetwork Traffic and Congestion Control
Canadian institutionsCarleton University
Fundersnot available
KeywordsMulticastComputer scienceComputer networkDistributed computingSource-specific multicastInter-domainMultiprotocol Label SwitchingProtocol Independent MulticastXcastUnicastIP multicastPragmatic General MulticastMulticast addressScalabilityTree (set theory)Single point of failureQuality of service

Abstract

fetched live from OpenAlex

Establishing multicast communications in MPLS-capable networks is an essential requirement for a wide-scale deployment of MPLS in the Internet. This paper outlines a framework for the setup of a MultiPoint-to-MultiPoint (MP2MP) Label Switched Path (LSP) for establishing uni-directional multicast shared trees. The presented framework is intended for multicast applications within a single autonomous domain and can be extended to cover inter-domain multicast sessions. We propose the use of one (or more) control points in the network called Rendez-vous Points (RP) in a manner similar to PIM-SM shared trees. Senders of the multicast session have to register with the RP and establish unicast LSPs with the RP. Receivers who join the session have to send their join requests to the RP which acts as a root (and the sender) of a one-to-many tree by establishing a Point-to-MultiPoint (P2MP) LSP between the RP and the receiver. This architecture utilizes more than one RP to implement RP failure recovery, to provide load balancing within the domain, and to enable the extension of this framework to multiple domains by establishing LSPs between RPs in different domains. This architecture also has the advantage of using existing MPLS techniques and existing routing protocols and requires only the addition of more management capabilities at the RPs. The paper explains the framework in details and provides an example on how to set the LSP on a given topology. We also refer to some preliminary simulation results testing the scalability of the architecture in comparison with traditional multicast routing.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.881
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.013
GPT teacher head0.235
Teacher spread0.222 · 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.

Study designTheoretical or conceptual
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

Citations4
Published2004
Admission routes1
Has abstractyes

Explore more

Same venueProceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIESame topicNetwork Traffic and Congestion ControlFrench-language works237,207