{"id":"W3035153683","doi":"10.48550/arxiv.2006.08774","title":"Optimal Virtual Network Function Deployment for 5G Network Slicing in a Hybrid Cloud Infrastructure","year":2020,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Software-Defined Networks and 5G","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; Horizon 2020 Framework Programme; Canada Research Chairs","keywords":"Computer science; Virtual network; Cloud computing; Distributed computing; Virtualization; Software deployment; Heuristic; Resource allocation; Network virtualization; Computer network","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":[0.001008833,0.001033355,0.0009032948,0.0004214523,0.0004549183,0.0009053723,0.0006603364,0.000889609,0.00233566],"category_scores_gemma":[0.002396918,0.0004333292,0.0005037813,0.0005119811,0.0007185952,0.0009544403,0.0007807189,0.0007011631,0.0001544393],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001576108,"about_ca_system_score_gemma":0.001391464,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007326817,"about_ca_topic_score_gemma":0.006246463,"domain_scores_codex":[0.9995922,0.0001711868,0.000009709814,0.00005757894,0.00004350998,0.0001258135],"domain_scores_gemma":[0.9989896,0.000707355,0.0001016146,0.00004023599,0.00006878544,0.00009238111],"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":[0.00007319015,0.00001948805,0.0003305607,0.0000295397,0.00001073213,0.00004007874,0.00001264928,0.9888586,0.0008605746,0.004087408,0.0003649098,0.005312361],"study_design_scores_gemma":[0.000005954878,0.00001932723,0.00008669525,0.000003359312,0.000003834718,0.000007541554,0.00001571643,0.9980458,0.0002065791,0.001488356,0.0001147402,0.000001981771],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1956462,0.0008406292,0.7950733,0.000517931,0.00007806705,0.000166892,0.0002136812,0.0002555478,0.007207824],"genre_scores_gemma":[0.9002289,0.0002356849,0.09834287,0.00006008505,0.00001759132,0.00006354992,0.00009519506,0.00004316215,0.0009130402],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007326817,"threshold_uncertainty_score":0.01456833,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03860374728414589,"score_gpt":0.1787090559101535,"score_spread":0.1401053086260076,"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."}}