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SD-FAST: A Packet Rerouting Architecture in SDN

2019· article· en· W3009488744 on OpenAlexaff
M. A. Moyeen, Fangye Tang, Dipon Saha, Israat Haque

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldComputer Science
TopicSoftware-Defined Networks and 5G
Canadian institutionsDalhousie University
Fundersnot available
KeywordsOpenFlowComputer scienceComputer networkBacktrackingNetwork packetNetwork topologySoftware-defined networkingForwarding planeTraversePath (computing)Distributed computingReal-time computingAlgorithm

Abstract

fetched live from OpenAlex

Communication link failure is common in any network. In Software Defined Network (SDN), protection-based recovery scheme reduces the failure recovery delay by installing alternative routes at the data plane switches. We can deploy Fast Failure Group (FFG) of OpenFlow protocol if a switch has an alternative path towards the destination; otherwise, the switch can use crankback approach to send the affected traffic towards the traversed route to find an alternative path. These existing recovery schemes force every packet to traverse a chain of matching tables even in the absence of a link failure, which impacts packet processing time and end-to-end delay. In this paper, we propose a packet rerouting architecture, called SD-FAST, that invokes recovery scheme only after facing failure and reduces both the packet processing and crankback backtracking time. We evaluate SD-FAST in Mininet, considering real and simulated traffic on real network topologies. The evaluation results confirm that SD-FAST can reduce around 73% crankback backtracking time and 64% delay compared to its counterparts.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.573
Threshold uncertainty score0.366

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 head0.005
GPT teacher head0.200
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

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 designObservational
Domainnot available
GenreEmpirical

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

Citations8
Published2019
Admission routes1
Has abstractyes

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