{"id":"W4238078233","doi":"10.4018/978-1-7998-5339-8.ch083","title":"Resource Provisioning and Scheduling of Big Data Processing Jobs","year":2021,"lang":"en","type":"book-chapter","venue":"IGI Global eBooks","topic":"Cloud Computing and Resource Management","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Cloud computing; Provisioning; Big data; Computer science; Scheduling (production processes); Data processing; Resource (disambiguation); Distributed computing; Data science; Database; Operating system; Engineering; Computer network; Operations management","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":[0.0002831444,0.000589338,0.0004336825,0.0004101115,0.0007041862,0.001820025,0.0009512134,0.0004905494,0.006805369],"category_scores_gemma":[0.0005174298,0.0004584018,0.0004145528,0.001056422,0.0002230843,0.001054312,0.000693734,0.001114264,0.003966644],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006989767,"about_ca_system_score_gemma":0.001152681,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001560293,"about_ca_topic_score_gemma":0.002739395,"domain_scores_codex":[0.9997898,0.00003252929,0.00001145226,0.00003798763,0.00009173771,0.00003650477],"domain_scores_gemma":[0.999848,0.00005627561,0.0000101703,0.00002425135,0.00003116067,0.00003021331],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000346646,0.0003095594,0.0008728819,0.001692828,0.0000499752,0.0006849506,0.0005970764,0.1203866,0.04992171,0.1261043,0.1722446,0.5267889],"study_design_scores_gemma":[0.00005203225,0.0001522637,0.002117365,0.0004282497,0.00002286369,0.0005211903,0.0003871108,0.3255435,0.02064413,0.07684355,0.5732179,0.00006988522],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04666461,0.03547323,0.5893945,0.004461652,0.005696286,0.001228163,0.00305642,0.005510979,0.3085142],"genre_scores_gemma":[0.2653952,0.03079486,0.5227094,0.00118131,0.001478035,0.0006484294,0.003711964,0.001725987,0.1723548],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006805369,"threshold_uncertainty_score":0.02276617,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04310120358457541,"score_gpt":0.2574656598287602,"score_spread":0.2143644562441848,"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."}}