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Record W1577013748 · doi:10.1109/pacrim.2001.953527

Routing reliability analysis of partially disjoint paths

2002· article· en· W1577013748 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
FieldComputer Science
TopicSoftware Testing and Debugging Techniques
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsComputer scienceComputer networkStatic routingEqual-cost multi-path routingOpen Shortest Path FirstLink-state routing protocolRouting protocolDynamic Source RoutingRouting Information ProtocolZone Routing ProtocolMultipath routingEnhanced Interior Gateway Routing ProtocolReliability (semiconductor)Distributed computingPath vector protocolRouting (electronic design automation)

Abstract

fetched live from OpenAlex

Alternative paths may significantly improve routing reliability in an IP network, One application of this technique is to enhance the reliability of the popular open shortest path first (OSPF) routing protocol. In our proposed reliable OSPF (ROSPF) routing protocol, one primary path and two alternate backup paths are deployed for data transmission. As expected, the number of shared links and routers among the three paths dominates the reliability of the routing connection between two routers. The calculation of routing reliability of multiple paths is very important in alternate path-finding algorithms. To solve this problem, we use the Venn diagram model to analyze the overall failure probability of three partially disjoint paths and to understand how the double- and triple-shared links affect the routing reliability. General mathematical formulas to calculate the failure probability are also obtained.

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)0.001
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 score0.958
Threshold uncertainty score0.263

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 science0.0000.000
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 head0.031
GPT teacher head0.257
Teacher spread0.226 · 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