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Record W4312643471 · doi:10.1109/tii.2022.3216568

Dataplane-Based Fast Failover in SDN-Enabled Wide Area Measurement System of Smart Grid

2022· article· en· W4312643471 on OpenAlexafffund
Tong Duan, Venkata Dinavahi

Bibliographic record

VenueIEEE Transactions on Industrial Informatics · 2022
Typearticle
Languageen
FieldComputer Science
TopicSoftware-Defined Networks and 5G
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of CanadaNational Natural Science Foundation of China
KeywordsFailoverBackupPhasorComputer scienceAlgorithmNetwork topologyComputer networkDistributed computingTheoretical computer scienceTopology (electrical circuits)MathematicsDatabase

Abstract

fetched live from OpenAlex

In the wide area measurement system (WAMS) of smart grid, the real-time monitoring and protection applications have stringent requirements for the end-to-end transmission delays between phasor measurement units and phasor data concentrator, and fast failover (FF) is required to ensure the communication performance after link failures. In this work, the software-defined network (SDN) technology is utilized to enable datapath failover upon a link failure with a global view of the communication network. Then, a novel dataplane-based fast failover (DFF) mechanism is proposed to <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">directly</i> reroute the data packet in dataplane without interacting with the SDN controller. Based on the mathematical analysis over the WAMS topology features, the proposed DFF optimizes two procedures of failover: backup path construction and backup path installation. Using the proposed backup path construction algorithms, the 3-approximate and (1+2 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\varepsilon$</tex-math></inline-formula> )-approximate ( <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$0&lt; \varepsilon &lt; 1$</tex-math></inline-formula> ) backup paths can be constructed, theoretically guaranteeing the data transmission delays both <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">during</i> and <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">after</i> failover. Using the proposed LinkID-based FF group table installation method, the conflict of forwarding rules between original and backup paths can be eliminated, while the storage cost is also optimized. The simulation results on six IEEE benchmark test power systems show that the proposed DFF mechanism could achieve lower data transmission delays during and after failover compared with the existing control plane based and dataplane-based failover mechanisms.

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)0.001
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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.987
Threshold uncertainty score0.864

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 communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.060
GPT teacher head0.217
Teacher spread0.158 · 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
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

Citations12
Published2022
Admission routes2
Has abstractyes

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