{"id":"W4312850770","doi":"10.1109/meditcom55741.2022.9928752","title":"Online and Scalable Virtual Network Functions Chain Placement for Emerging 5G Networks","year":2022,"lang":"en","type":"article","venue":"","topic":"Software-Defined Networks and 5G","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ciena (Canada); École de Technologie Supérieure; Carleton University","funders":"","keywords":"Computer science; Virtual network; Scalability; Distributed computing; Integer programming; Cloud computing; Slicing; Enhanced Data Rates for GSM Evolution; Linear programming; Heuristic; Set (abstract data type); Computer network; Algorithm; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":false,"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":[0.000774978,0.001069228,0.0008567456,0.000471706,0.0007979376,0.0009925015,0.001058361,0.000777449,0.003309927],"category_scores_gemma":[0.001560018,0.0004269626,0.0004179243,0.0008412781,0.0005220977,0.001203592,0.001090977,0.000771788,0.0003227942],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001459953,"about_ca_system_score_gemma":0.001494657,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006132263,"about_ca_topic_score_gemma":0.008913802,"domain_scores_codex":[0.9994487,0.000197056,0.0000207306,0.0001012316,0.00009978389,0.0001323736],"domain_scores_gemma":[0.9993581,0.0003294947,0.00008871189,0.00007260042,0.00007895084,0.00007206787],"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":[0.00008832556,0.00004706417,0.0003715128,0.00007174827,0.00001200066,0.0001093465,0.0000478128,0.9465122,0.002039437,0.007398138,0.00160775,0.04169481],"study_design_scores_gemma":[0.000006378783,0.0000260671,0.00005020623,0.000004463887,0.000003208227,0.00001998203,0.00003372526,0.9959254,0.0004762667,0.003001599,0.0004492576,0.00000344311],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03928005,0.0004430616,0.9559008,0.0002541163,0.00007579999,0.0001257778,0.00009737441,0.0004582761,0.003364587],"genre_scores_gemma":[0.7559617,0.0004476569,0.2415106,0.00007174617,0.00003819135,0.0001104098,0.0001941348,0.00006765922,0.001597822],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006132263,"threshold_uncertainty_score":0.01219314,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01415170663386162,"score_gpt":0.2290887517234637,"score_spread":0.2149370450896021,"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."}}