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Record W2109226510 · doi:10.1109/icton.2009.5185138

A new approach to node-failure protection with span-protecting p-cycles

2009· article· en· W2109226510 on OpenAlex

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

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvanced Optical Network Technologies
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsSurvivabilitySpare partNode (physics)Span (engineering)Computer sciencePath (computing)Computer networkRing networkSet (abstract data type)GeneralizationTopology (electrical circuits)MathematicsCombinatoricsNetwork topologyEngineeringStructural engineering

Abstract

fetched live from OpenAlex

Recent work has revealed a new, relatively simple and possibly cost-effective, approach to achieve combined protection of optical networks against both node and span failures. The resulting network designs use only a single set of p-cycle structures that have the same or only slightly more capacity than a corresponding optimal set of p-cycles for span protection. The new principle is based on a generalization of how nodes in a BLSR-ring or p-cycle (to date) derive survivability through loop-back at the nearest two neighbour-nodes on the same ring. The generalization views any combination of node failure and an affected transiting path from the standpoint of the two-hop segment defined by the failure node, and the nodes immediately adjacent on the affected path. We then ask whether these nodes are found together within the same p-cycle as the failure node, or another p-cycle entirely. In any case where they are, we show that the transiting path affected by the node failure is inherently restorable by ordinary p-cycle switching actions whether the respective two-hop segment is on-cycle, straddling, or partially on-cycle and partially straddling. We explain the principle and characterize its effectiveness in terms of network-wide single node failure restorability (R <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1-node</sub> ) in networks designed only for minimum spare capacity, networks designed for enhanced R <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1-node</sub> (at min capacity) and networks designed strictly for R <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1-node</sub> = 1.

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)0.000
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: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.412
Threshold uncertainty score0.541

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 head0.013
GPT teacher head0.208
Teacher spread0.195 · 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

Quick stats

Citations21
Published2009
Admission routes1
Has abstractyes

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