{"id":"W4417436617","doi":"10.1016/j.comcom.2025.108340","title":"Power prediction and energy aware placement of containers over virtual machines","year":2025,"lang":"en","type":"article","venue":"Computer Communications","topic":"Cloud Computing and Resource Management","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"Mitacs","keywords":"Cloud computing; Testbed; Energy consumption; Virtual machine; Live migration; Efficient energy use; Scalability; Energy (signal processing)","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0004739706,0.0006382771,0.0005495931,0.000345128,0.0003284236,0.0006823874,0.0008445853,0.0005168191,0.0008274264],"category_scores_gemma":[0.001543473,0.0003632311,0.000300441,0.0004053007,0.0003915585,0.0008354158,0.000327989,0.0005504101,0.0002377586],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008447884,"about_ca_system_score_gemma":0.000757773,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0077608,"about_ca_topic_score_gemma":0.008790843,"domain_scores_codex":[0.9997827,0.00005487318,0.000009559768,0.00006282979,0.00003435206,0.00005572886],"domain_scores_gemma":[0.9994736,0.0002200271,0.00009748265,0.00005432716,0.0001139388,0.00004072674],"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":[0.00004434917,0.00002895708,0.001545947,0.000009584075,0.000005902556,0.00001515865,0.000008927038,0.9872832,0.001008435,0.0003016629,0.0003254728,0.009422303],"study_design_scores_gemma":[7.673028e-7,0.000004962844,0.0001190816,5.733825e-7,7.868641e-7,0.000001573801,0.00000249297,0.9994193,0.0002526661,0.0001637148,0.00003343758,6.672752e-7],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4926853,0.0003853031,0.5011519,0.000557874,0.0001418174,0.00007483145,0.0002279264,0.001390375,0.00338464],"genre_scores_gemma":[0.9731426,0.00006144712,0.02571671,0.00003448877,0.00001286379,0.00002104291,0.00008441192,0.00003425924,0.0008920979],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0077608,"threshold_uncertainty_score":0.01543123,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008934456302681188,"score_gpt":0.2439694468743871,"score_spread":0.2350349905717059,"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."}}