{"id":"W2170560434","doi":"10.1109/tpds.2013.227","title":"Optimal Load Balancing and Energy Cost Management for Internet Data Centers in Deregulated Electricity Markets","year":2013,"lang":"en","type":"article","venue":"IEEE Transactions on Parallel and Distributed Systems","topic":"Cloud Computing and Resource Management","field":"Computer Science","cited_by":49,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Zhejiang University","keywords":"Computer science; Queueing theory; Electricity; Heuristic; Service-level agreement; Service provider; Energy consumption; Quality of service; Load balancing (electrical power); Service (business); The Internet; Computer network; Constraint (computer-aided design); Load management; Transmission (telecommunications); Telecommunications; Business; 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":[0.001431419,0.001010582,0.001240211,0.000771108,0.0008112005,0.002165563,0.001352104,0.001375574,0.002456831],"category_scores_gemma":[0.00287602,0.0008517048,0.0003847822,0.001027397,0.0007884687,0.001923942,0.000942123,0.001095226,0.0002216946],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002694339,"about_ca_system_score_gemma":0.002083448,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01136977,"about_ca_topic_score_gemma":0.0128493,"domain_scores_codex":[0.9993669,0.0002634372,0.00001655015,0.0001054425,0.00009991695,0.0001476953],"domain_scores_gemma":[0.9990813,0.000618476,0.0001182796,0.0000200964,0.00009856255,0.00006333248],"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":[0.00005676075,0.00003962625,0.0001857485,0.0000295156,0.00001020504,0.00002735123,0.00001700852,0.9873936,0.0003760456,0.004515692,0.0004714716,0.006876866],"study_design_scores_gemma":[0.000007878308,0.000008737449,0.00004310262,0.000001473548,0.000002082781,0.000002171126,0.00001029849,0.9981476,0.00009209766,0.001588657,0.00009392255,0.000001930453],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1975894,0.001076795,0.7860906,0.001288102,0.00008827781,0.0002834467,0.0002405684,0.0003053118,0.01303763],"genre_scores_gemma":[0.9546052,0.0003188991,0.04275329,0.00007805977,0.00002895167,0.0001269228,0.00008334109,0.00005386204,0.001951523],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01136977,"threshold_uncertainty_score":0.02260715,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01545229402561011,"score_gpt":0.2215913520750589,"score_spread":0.2061390580494488,"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."}}