MétaCan
Menu
Back to cohort
Record W2001440284 · doi:10.1109/drcn.2009.5340010

Service overlay network design with reliability constraints

2009· article· en· W2001440284 on OpenAlexaff
Ngok Lam, L.G. Mason, Zbigniew Dziong

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicNetwork Traffic and Congestion Control
Canadian institutionsÉcole de Technologie SupérieureMcGill University
Fundersnot available
KeywordsComputer scienceOverlayOperabilityOverlay networkMathematical optimizationNetwork planning and designLagrange multiplierReliability (semiconductor)Key (lock)Context (archaeology)Optimization problemDistributed computingSet (abstract data type)Service (business)Reliability engineeringComputer networkEngineeringMathematicsThe Internet

Abstract

fetched live from OpenAlex

We studied a class of Service Overlay Network (SON) design problem with reliability constraints. It is assumed that a SON network could enter an inadmissible status for two reasons; first when there is insufficient resource to accommodate new connections, second when some hardware devices malfunction. The design problem is usually formulated as either a Maximum Profit (MP) constrained optimization problem or a Minimum Cost (MC) constrained optimization problem. In this article we investigate the relationship between the two formulations in the context of ensuring system operability. By using the set of Lagrange multipliers from the MC formulation as a tool, we show the general condition that MP and MC give exactly the same network designs. The key contribution of this paper is the provision of insight into the solution nature of the MP and the MC formulations in designing a reliable overlay network, thereby giving guidelines to the proper formulation the network designers may consider in designing a reliable yet economically optimal SON network.

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 score0.819
Threshold uncertainty score0.407

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 science0.0010.000
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 head0.011
GPT teacher head0.205
Teacher spread0.194 · 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

Citations2
Published2009
Admission routes1
Has abstractyes

Explore more

Same topicNetwork Traffic and Congestion ControlFrench-language works237,207