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Record W2007844438 · doi:10.1109/ecumn.2007.53

Toward a Distributed Control Plane Architecture for Next Generation Routers

2007· article· en· W2007844438 on OpenAlexaff
Kim Khoa Nguyen, Hicham Mahkoum, B. Jaumard, Chadi Assi, Matthew Lanoue

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicSoftware-Defined Networks and 5G
Canadian institutionsConcordia University
Fundersnot available
KeywordsComputer scienceComputer networkDistributed computingScalabilityMultiprotocol Label SwitchingRouting protocolRouterForwarding planeRouting (electronic design automation)Quality of serviceOperating system

Abstract

fetched live from OpenAlex

As networks become more and more pervasive and broadband access technologies evolve to provide affordable broadband solutions for both homes and offices, one needs to rethink the architecture design for next generation routers in order to be able to deliver multiple services over high-speed interfaces and perform fast switching capabilities (e.g., multi-petabit). The size and complexity of next generation networks requires a protocol transition from its classical centralized approach to a fully distributed and scalable paradigm. In this paper, we propose a new control plane architecture that is resilient and scalable where we distribute the OSPF/IS-IS, MPLS and BGP protocols using IETF-approved inter-protocol interfaces. In such architecture, forwarding tables will be updated by OSPF, IS-IS, RTM, BGP and MPLS routing protocols distributed onto multiple processors, in the interface cards themselves. We therefore revisit each of these protocols and redraw their implementation within an efficient, scalable, distributed, resilient, and fault tolerant scheme. As a proof of concept, we present the Hyperchip router (PBR1280) that has been built on these grounds and discuss the performance of the proposed distributed architecture. Although some features (e.g., resiliency) still need further development, it is shown that the proposed distributed routing protocol scheme already offers a new generation of routers with significant higher switching capacity.

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)0.000
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: Methods · Consensus signal: none
Teacher disagreement score0.887
Threshold uncertainty score0.371

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 head0.038
GPT teacher head0.242
Teacher spread0.204 · 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.

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

Citations17
Published2007
Admission routes1
Has abstractyes

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