{"id":"W2015213058","doi":"10.1109/infocom.2014.6847950","title":"Venice: Reliable virtual data center embedding in clouds","year":2014,"lang":"en","type":"article","venue":"","topic":"Cloud Computing and Resource Management","field":"Computer Science","cited_by":124,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Cloud computing; Data center; Provisioning; Quality of service; Distributed computing; Scheduling (production processes); High availability; Embedding; Reliability (semiconductor); Virtual machine; Computer network; Service (business); Server; Database; 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":[0.0005828314,0.0004732023,0.0003862486,0.0003891609,0.0005242844,0.0007504706,0.00122695,0.0004568149,0.0009805346],"category_scores_gemma":[0.001745332,0.0002524916,0.0003056402,0.0003741696,0.0006269615,0.001267447,0.001713456,0.0007305252,0.0002159536],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004782678,"about_ca_system_score_gemma":0.0008795547,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001672721,"about_ca_topic_score_gemma":0.002347525,"domain_scores_codex":[0.9993663,0.0001540243,0.00002335632,0.00007581996,0.0002394846,0.0001409948],"domain_scores_gemma":[0.9993368,0.0001450912,0.00009093147,0.0002120557,0.0001130707,0.0001020817],"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":[0.000467631,0.000229055,0.003044124,0.0002297891,0.00008420747,0.000468997,0.0002656825,0.670158,0.04127523,0.05616703,0.008303932,0.2193062],"study_design_scores_gemma":[0.00001991536,0.0001111925,0.0004146698,0.0000139053,0.00001303536,0.0001496655,0.00005921725,0.9723776,0.01206283,0.009744393,0.005011219,0.00002233776],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1011989,0.0007883696,0.8881755,0.0002684414,0.0001311348,0.0001267434,0.00006796841,0.004003623,0.005239338],"genre_scores_gemma":[0.8453071,0.0002141352,0.1526301,0.00006762752,0.00002407599,0.0000414265,0.0001100089,0.0001182128,0.00148735],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001672721,"threshold_uncertainty_score":0.003470063,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02115739651338074,"score_gpt":0.2681912636423378,"score_spread":0.2470338671289571,"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."}}