{"id":"W2153436173","doi":"10.1109/ccgrid.2012.47","title":"Optimal Reconfiguration of the Cloud Network for Maximum Energy Savings","year":2012,"lang":"en","type":"article","venue":"","topic":"Cloud Computing and Resource Management","field":"Computer Science","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Provisioning; Cloud computing; Computer science; Heuristics; Distributed computing; Energy consumption; Data center; Server; Cloudlet; Integer programming; Computer network; Operating system; Algorithm; 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":[0.0002695411,0.000807771,0.0005213286,0.0004597779,0.0006480709,0.0009029214,0.000591403,0.0006319938,0.001579935],"category_scores_gemma":[0.001030546,0.0003605856,0.000289203,0.0004439299,0.0003868683,0.0008536795,0.0004136097,0.0004340632,0.0002270083],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001202219,"about_ca_system_score_gemma":0.001100955,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003867846,"about_ca_topic_score_gemma":0.007834552,"domain_scores_codex":[0.9997018,0.00008114761,0.000009719513,0.00005217275,0.00003754477,0.0001174959],"domain_scores_gemma":[0.999702,0.0001179693,0.00006601321,0.00003546257,0.00003541205,0.00004312814],"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":[0.0000699613,0.00003357958,0.000304853,0.00003495586,0.00001035115,0.0000813411,0.00003079967,0.9757248,0.0074797,0.003282118,0.0008097686,0.01213779],"study_design_scores_gemma":[0.000009017245,0.00003474116,0.0002241406,0.000004959242,0.000007347045,0.00003095892,0.00004780743,0.995198,0.001580305,0.002443461,0.0004139115,0.00000540578],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3590575,0.001060076,0.6137472,0.001019822,0.0001495136,0.0002375608,0.0001952146,0.0008441956,0.02368902],"genre_scores_gemma":[0.9711395,0.0001599792,0.02748347,0.00005786717,0.00001333824,0.00003744075,0.00004241646,0.00003550354,0.001030455],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003867846,"threshold_uncertainty_score":0.008722782,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01334201777479501,"score_gpt":0.2149447433806295,"score_spread":0.2016027256058345,"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."}}