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Record W2167420935 · doi:10.1109/aina.2007.41

Automating Overlay Networks Management

2007· article· en· W2167420935 on OpenAlex
Ibrahim Al‐Oqily, A. Karmouch

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueProceedings · 2007
Typearticle
Languageen
FieldComputer Science
TopicPeer-to-Peer Network Technologies
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsOverlayOverlay networkComputer scienceComputer networkContext (archaeology)ArchitectureDistributed computingLayer (electronics)Set (abstract data type)EnforcementWorld Wide WebOperating systemThe Internet

Abstract

fetched live from OpenAlex

This paper proposes a context-aware policy-based architecture that automates the management of overlay networks. The objective of this architecture is to form a policy layer above the overlay layer. The policy layer consists of a set of overlay policy enforcement points and an overlay policy decision point that cooperate to dynamically adapt the behavior of the overlay network to the preferences of the user, the network and the service providers. With this contribution to overlay networks, policies are generated dynamically at run time from the available context information and enforced on the fly. This paper describes our novel architecture, its advantages, and the simulation results that varify its effectiveness.

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.

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: Other design · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.679
Threshold uncertainty score0.652

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 science0.0010.001
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 head0.007
GPT teacher head0.232
Teacher spread0.225 · 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