{"id":"W2485763679","doi":"10.4018/978-1-4666-4522-6.ch011","title":"Energy-Efficiency in Cloud Data Centers","year":2013,"lang":"en","type":"book-chapter","venue":"Advances in systems analysis, software engineering, and high performance computing book series","topic":"Cloud Computing and Resource Management","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Cloud computing; Data center; Computer science; Energy consumption; Virtualization; Server; Efficient energy use; Distributed computing; Wireless sensor network; Computer network; Software deployment; Engineering; 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":[0.0004703734,0.0006616669,0.000711801,0.0007348792,0.0007091117,0.002461225,0.0012692,0.0006406601,0.004310613],"category_scores_gemma":[0.001025919,0.0003435048,0.0004783135,0.001793627,0.0005936631,0.002254533,0.001175328,0.0009926235,0.0009634624],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002443001,"about_ca_system_score_gemma":0.001004007,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002759555,"about_ca_topic_score_gemma":0.001859896,"domain_scores_codex":[0.9995215,0.00006192187,0.00001470629,0.00007545761,0.0002167269,0.0001097462],"domain_scores_gemma":[0.9997351,0.0001000433,0.00001672582,0.00004010445,0.00008479139,0.00002331154],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001745412,0.0001444893,0.0008263473,0.0005464896,0.00005318999,0.0002043062,0.0002065012,0.1359347,0.006318371,0.5811738,0.02547122,0.2489459],"study_design_scores_gemma":[0.00004933021,0.0001301295,0.002501806,0.0004207227,0.00005064931,0.0003278909,0.0004337512,0.4442699,0.01575405,0.3599158,0.1760886,0.00005739177],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08970545,0.1019577,0.4289936,0.006390638,0.001405842,0.0002879573,0.0005283193,0.001374048,0.3693564],"genre_scores_gemma":[0.8705942,0.02923486,0.05278968,0.0004680296,0.0004332924,0.0001388785,0.0002885689,0.0004511139,0.04560138],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004310613,"threshold_uncertainty_score":0.01772529,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007218522069936254,"score_gpt":0.1993873398393454,"score_spread":0.1921688177694091,"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."}}