{"id":"W2011685880","doi":"10.1109/tpds.2012.205","title":"SyRaFa: Synchronous Rate and Frequency Adjustment for Utilization Control in Distributed Real-Time Embedded Systems","year":2012,"lang":"en","type":"article","venue":"IEEE Transactions on Parallel and Distributed Systems","topic":"Real-Time Systems Scheduling","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Fonds Québécois de la Recherche sur la Nature et les Technologies; Natural Sciences and Engineering Research Council of Canada; University of Nebraska-Lincoln","keywords":"Computer science; Workload; Setpoint; Asynchronous communication; Frequency scaling; Task (project management); Synchronization (alternating current); Distributed computing; Multi-core processor; Quality of service; Real-time computing; Parallel computing; Computer network; Operating system; Energy consumption","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.001375153,0.0004732195,0.0008325566,0.0002416591,0.0003482998,0.0003935308,0.0003213056,0.0003000704,0.000004094836],"category_scores_gemma":[0.00002960906,0.0004358297,0.0001151571,0.000520846,0.00007713534,0.00108162,0.000006124668,0.0002058933,0.00002847466],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003306269,"about_ca_system_score_gemma":0.0001044973,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009384877,"about_ca_topic_score_gemma":0.00002400629,"domain_scores_codex":[0.9964166,0.0006459217,0.001025012,0.0007271453,0.0003349882,0.0008503351],"domain_scores_gemma":[0.9978331,0.0005671995,0.0003537658,0.0006201166,0.0001944488,0.0004313936],"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":[0.0004324302,0.001409386,0.001628274,0.001777695,0.0006570705,0.00003713902,0.001773955,0.9562772,0.01525089,0.01697405,0.001074689,0.002707247],"study_design_scores_gemma":[0.003975242,0.0002890271,0.002274079,0.0003847193,0.0001081172,0.0001629774,0.0005396887,0.9912322,0.000117473,0.00007924152,0.0001995207,0.000637771],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01823091,0.002251138,0.9737942,0.0001062385,0.001540321,0.002558277,0.001147693,0.0002942044,0.00007699362],"genre_scores_gemma":[0.9972616,0.0002051858,0.000952657,0.00001771901,0.0001392556,0.001106372,0.000193546,0.00003385553,0.00008975519],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9790307,"threshold_uncertainty_score":0.9998093,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02285363525884347,"score_gpt":0.2558623161601467,"score_spread":0.2330086809013032,"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."}}