{"id":"W3009832548","doi":"10.1109/globecom38437.2019.9013429","title":"On Dynamic Mapping and Scheduling of Service Function Chains in SDN/NFV-Enabled Networks","year":2019,"lang":"en","type":"article","venue":"","topic":"Software-Defined Networks and 5G","field":"Computer Science","cited_by":30,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Distributed computing; Virtual network; Scheduling (production processes); Provisioning; Computer network; Quality of service; Software-defined networking; Network Functions Virtualization; Integer programming; Cloud computing; Mathematical optimization; Algorithm; Operating system","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":[0.001217638,0.0008551055,0.0007872792,0.0004498574,0.0008377794,0.0007653419,0.0008790809,0.0005183675,0.001301057],"category_scores_gemma":[0.002334989,0.0004016468,0.0004036193,0.0006670252,0.0007077277,0.0008911183,0.0009498743,0.0007701236,0.0001251892],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00122815,"about_ca_system_score_gemma":0.001730302,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007077541,"about_ca_topic_score_gemma":0.006476275,"domain_scores_codex":[0.9993269,0.0002660402,0.00002734144,0.0001094391,0.0001239432,0.0001463536],"domain_scores_gemma":[0.9991229,0.0005198886,0.0001137169,0.00006285914,0.00009544903,0.00008523948],"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":[0.00005087342,0.00003286528,0.0002845331,0.00003821153,0.00001084212,0.00003879603,0.00004427203,0.9708306,0.001501133,0.007371748,0.0003141806,0.01948191],"study_design_scores_gemma":[0.000004282764,0.00002077396,0.000041572,0.000003169637,0.000002148018,0.000007699102,0.000009925131,0.9967158,0.0003477738,0.00255687,0.000287486,0.000002523007],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0494296,0.0003729541,0.9475771,0.0002126403,0.00004494241,0.0000952414,0.00004048388,0.0001208375,0.002106288],"genre_scores_gemma":[0.7850541,0.0005486436,0.2123503,0.0000804388,0.00005185902,0.0001692124,0.0001287888,0.00005340049,0.001563207],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007077541,"threshold_uncertainty_score":0.01407272,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007403872125987177,"score_gpt":0.1970784326233636,"score_spread":0.1896745604973764,"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."}}