{"id":"W3193468109","doi":"10.1109/tnse.2021.3104499","title":"Fault-Resilience for Bandwidth Management in Industrial Software-Defined Networks","year":2021,"lang":"en","type":"article","venue":"IEEE Transactions on Network Science and Engineering","topic":"Software-Defined Networks and 5G","field":"Computer Science","cited_by":69,"is_retracted":false,"has_abstract":true,"ca_institutions":"Brandon University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Testbed; Software-defined networking; Bandwidth (computing); Computer network; Dynamic bandwidth allocation; Distributed computing; Resilience (materials science); Network management; Software; Operating system","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001821692,0.0004838712,0.0003354219,0.000776758,0.0005474049,0.001060392,0.001185719,0.0005072854,0.000669021],"category_scores_gemma":[0.003109953,0.0001610011,0.0002411139,0.0004230108,0.0007184339,0.001335491,0.0009043433,0.0006981878,0.0001237993],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001087529,"about_ca_system_score_gemma":0.0010834,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002380788,"about_ca_topic_score_gemma":0.001483485,"domain_scores_codex":[0.9986267,0.0003951963,0.0001007871,0.0001806166,0.0005420382,0.0001546333],"domain_scores_gemma":[0.9987187,0.0004386561,0.0001985106,0.0002729247,0.000297524,0.00007375967],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004828872,0.0002777604,0.005633415,0.0004796741,0.0001111961,0.0004133649,0.0004802433,0.4801163,0.07577666,0.06314705,0.003434195,0.3696472],"study_design_scores_gemma":[0.00002210417,0.0001461403,0.001075194,0.00004212454,0.00003906211,0.0001528454,0.00008027048,0.9514248,0.02844755,0.01065394,0.007889874,0.00002602728],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1447665,0.002558883,0.8447351,0.0006353307,0.0001511519,0.0001492939,0.00005968974,0.002574818,0.004369111],"genre_scores_gemma":[0.9405872,0.0003996265,0.05807094,0.00008344781,0.00003416526,0.00006823659,0.00007454726,0.00005189191,0.0006299014],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002380788,"threshold_uncertainty_score":0.009634197,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01550853885403095,"score_gpt":0.2197561723329692,"score_spread":0.2042476334789382,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}