{"id":"W2029494213","doi":"10.1109/cloudcom.2014.53","title":"VM Placement Algorithms for Hierarchical Cloud Infrastructure","year":2014,"lang":"en","type":"article","venue":"","topic":"Cloud Computing and Resource Management","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"","keywords":"Cloud computing; Computer science; Scalability; Node (physics); Distributed computing; Virtual machine; Software deployment; Cluster (spacecraft); Controller (irrigation); Multiple-criteria decision analysis; Architecture; Algorithm; Computer network; Operating system; Engineering","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":[0.00149265,0.0008795455,0.001051164,0.001494007,0.0008920498,0.0010363,0.001635981,0.001045472,0.003076107],"category_scores_gemma":[0.003008365,0.0005676564,0.0006994668,0.001653175,0.0005811429,0.001016133,0.001287682,0.000872881,0.000577366],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001780084,"about_ca_system_score_gemma":0.00179358,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007325417,"about_ca_topic_score_gemma":0.007890372,"domain_scores_codex":[0.9991593,0.000253801,0.00005254925,0.0001548163,0.0002259939,0.0001536015],"domain_scores_gemma":[0.9987555,0.0006364821,0.0001761492,0.00009744177,0.0002502881,0.0000842899],"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":[0.00006540862,0.00005879216,0.0006082715,0.00008573687,0.00002683706,0.00004438038,0.00007462863,0.8895887,0.001640234,0.008191434,0.001546008,0.09806955],"study_design_scores_gemma":[0.000009032287,0.00001557691,0.00007908712,0.000004395299,0.000003090427,0.00001219423,0.00001347898,0.9963952,0.0003185364,0.002841803,0.0003045502,0.000003075145],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01392269,0.0002413281,0.9833987,0.000105357,0.00003130763,0.0001294861,0.00005732776,0.0004177086,0.001696062],"genre_scores_gemma":[0.2770188,0.0002145924,0.7205085,0.00007336422,0.00003746438,0.0002080086,0.0001802019,0.00008091534,0.001678345],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007325417,"threshold_uncertainty_score":0.01456553,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01047286842945841,"score_gpt":0.2402160628955798,"score_spread":0.2297431944661214,"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."}}