{"id":"W2015750033","doi":"10.1109/icassp.2013.6638363","title":"Optimal task-level scheduling for cloud based multimedia applications","year":2013,"lang":"en","type":"article","venue":"","topic":"Cloud Computing and Resource Management","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Computer science; Distributed computing; Cloud computing; Scheduling (production processes); Two-level scheduling; Virtual machine; Dynamic priority scheduling; Schedule; Fair-share scheduling; Directed acyclic graph; Task analysis; Fixed-priority pre-emptive scheduling; Multimedia; Task (project management); Rate-monotonic scheduling; Operating system; Algorithm; Mathematical optimization","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":[0.0002026036,0.0001160475,0.0001057031,0.00007598347,0.0002029483,0.0001939496,0.0007834425,0.00004114089,0.00002958662],"category_scores_gemma":[0.00002296424,0.00009748621,0.00008372126,0.0002200544,0.00002702984,0.0000282261,0.0002380787,0.00006968797,0.0002870538],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002404122,"about_ca_system_score_gemma":0.00003003357,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003802793,"about_ca_topic_score_gemma":0.000001081193,"domain_scores_codex":[0.998973,0.00001740696,0.0001872413,0.0003686963,0.0001601609,0.0002935312],"domain_scores_gemma":[0.9990106,0.0001961107,0.00005806852,0.0005249551,0.0001025092,0.0001077512],"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":[0.000004220372,0.0003685495,0.0001708924,0.00008446755,0.00006191576,0.000001281204,0.0003999704,0.4194666,0.001429403,0.04450421,0.02624394,0.5072646],"study_design_scores_gemma":[0.0003604697,0.00002673666,0.0002714502,0.000006984999,0.000004502227,8.248638e-7,0.00003385253,0.9799569,0.0003582403,0.0005283584,0.01830576,0.0001459596],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.009344834,0.00002329174,0.9843744,0.002950314,0.0001752652,0.0008057891,0.000001548986,0.0003621481,0.00196242],"genre_scores_gemma":[0.1895319,2.021512e-7,0.8071952,0.0007815513,0.0002163809,0.0003861825,0.000003414225,0.000008705591,0.001876475],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.5604903,"threshold_uncertainty_score":0.3975373,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02396109780252659,"score_gpt":0.2487357781468084,"score_spread":0.2247746803442819,"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."}}