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Record W2155004989 · doi:10.1109/icc.2007.1058

Click on a Cluster: A Viable Approach to Scale Software-Based Routers

2007· article· en· W2155004989 on OpenAlexaff
Qiang Ye, M.H. MacGregor

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicSoftware-Defined Networks and 5G
Canadian institutionsUniversity of Alberta
FundersMichigan State University
KeywordsComputer scienceInfiniBandRouterForwarding planeScalabilityOperating systemNetwork packetComputer networkSoftwareLow latency (capital markets)Modular designLatency (audio)Embedded systemEmulation

Abstract

fetched live from OpenAlex

Extensible software-based routers running on commodity off-the-shelf hardware and open-source operating systems have been motivated by the progress in hardware technologies and by the demand for routers with new capabilities. The Click modular router is one such software system. Click provides a mechanism to extend packet processing functions while supporting higher packet forwarding performance compared with other software-based routers. However the limitation of executing on a PC is in tension with the requirement for higher performance. In this paper, we explore the scalability of an extended version of Click that runs on a cluster of PCs connected by a high-speed/low latency InfiniBand interconnection network. We present the implementation and evaluation of our prototype. Our measurements show that the performance of this router can be scaled nearly linearly with increasing cluster size.

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)0.000
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: Methods
Teacher disagreement score0.627
Threshold uncertainty score0.780

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.232
Teacher spread0.219 · 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

Citations3
Published2007
Admission routes1
Has abstractyes

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