{"id":"W4292291434","doi":"10.3390/electronics11162557","title":"Efficient Prioritization and Processor Selection Schemes for HEFT Algorithm: A Makespan Optimizer for Task Scheduling in Cloud Environment","year":2022,"lang":"en","type":"article","venue":"Electronics","topic":"Cloud Computing and Resource Management","field":"Computer Science","cited_by":90,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Job shop scheduling; Cloud computing; Scheduling (production processes); Workflow; Virtual machine; Distributed computing; Rate-monotonic scheduling; Mathematical optimization; Fair-share scheduling; Schedule; Operating system; Mathematics; Database","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006434971,0.0001342793,0.0001434208,0.0001302635,0.0004456806,0.00008541496,0.000265908,0.00003369739,0.000001824166],"category_scores_gemma":[0.00002378696,0.0001469394,0.00004824981,0.0002943189,0.00001417628,0.00001391616,0.0002495921,0.0001706591,4.99832e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003589846,"about_ca_system_score_gemma":0.00008206586,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001894285,"about_ca_topic_score_gemma":0.000002050694,"domain_scores_codex":[0.998581,0.00004775108,0.0002167013,0.0004853932,0.0002297104,0.0004394556],"domain_scores_gemma":[0.9995992,0.00007364605,0.0001022088,0.0001576939,0.00002749067,0.00003982909],"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":[0.00002495608,0.000142768,0.00003470423,0.00004250922,0.00001744555,5.258357e-7,0.0004818197,0.8929176,0.0002647073,0.004664031,0.00005829589,0.1013507],"study_design_scores_gemma":[0.0009763427,0.0003839846,0.00001842216,0.000009115496,0.00001087197,0.0000075199,0.00007438963,0.9408461,0.0004352197,0.0008451251,0.05622406,0.0001688059],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1156573,0.001939513,0.8804278,0.0008062929,0.0001239148,0.0009457001,0.000002785232,0.00008559079,0.00001109635],"genre_scores_gemma":[0.6153812,0.00006284947,0.3823775,0.0002875005,0.0002213004,0.001042519,0.00002072009,0.00004192873,0.0005644482],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.4997239,"threshold_uncertainty_score":0.5992016,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006721766661691908,"score_gpt":0.2179568641753416,"score_spread":0.2112350975136497,"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."}}