{"id":"W2970072511","doi":"10.1109/cloud.2019.00023","title":"Cloud VM Provisioning Using Analytical Performance Models","year":2019,"lang":"en","type":"article","venue":"","topic":"Cloud Computing and Resource Management","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Provisioning; Cloud computing; Computer science; Bottleneck; Virtual machine; Genetic algorithm; Distributed computing; Container (type theory); Workload; Minification; Computer network; Operating system; Engineering; Embedded 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":[0.0006667356,0.0009750336,0.0006903806,0.001040685,0.0006256576,0.001845522,0.001571937,0.001301659,0.003109682],"category_scores_gemma":[0.002758323,0.0005607928,0.0007856427,0.001366521,0.0004740239,0.001410321,0.000666427,0.0008179207,0.0008088782],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002360826,"about_ca_system_score_gemma":0.00170235,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01450482,"about_ca_topic_score_gemma":0.009184108,"domain_scores_codex":[0.9994019,0.0001791233,0.00001895955,0.00008207677,0.0001801167,0.0001377413],"domain_scores_gemma":[0.9991004,0.0004854757,0.0001396841,0.00005811738,0.0001758362,0.00004052367],"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":[0.000009216491,0.00001385831,0.0001530744,0.00001585693,0.000004998285,0.00001897649,0.00001161929,0.9922943,0.0001944489,0.004230571,0.0003708426,0.002682235],"study_design_scores_gemma":[0.00000101222,0.000002777251,0.00003583108,0.000003274412,0.000001576057,0.000004499437,0.000005104948,0.9985911,0.00005179183,0.001071218,0.0002300875,0.000001662227],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1156276,0.002312942,0.815518,0.001436132,0.0001528511,0.0003004253,0.0006829491,0.001279298,0.06268992],"genre_scores_gemma":[0.9277168,0.001355321,0.06046609,0.0001326664,0.00007399971,0.0002015621,0.0002541041,0.0001434404,0.009656097],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01450482,"threshold_uncertainty_score":0.02884078,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0258370183905096,"score_gpt":0.2419279519686328,"score_spread":0.2160909335781231,"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."}}