{"id":"W1913260600","doi":"10.1109/ccece.2003.1226374","title":"Implementing a high performance scheduling discipline WF2Q+ in FPGA","year":2004,"lang":"en","type":"article","venue":"","topic":"Network Traffic and Congestion Control","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Theratechnologies (Canada)","funders":"","keywords":"Weighted fair queueing; Generalized processor sharing; Computer science; Weighted round robin; Queueing theory; Fair queuing; Scheduling (production processes); Processor sharing; Network packet; Round-robin scheduling; Distributed computing; Computer network; Dynamic priority scheduling; Mathematical optimization; Quality of service","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":[0.0005461942,0.0005278164,0.000317421,0.0005218285,0.0003954359,0.0009085654,0.00132526,0.0003580456,0.004807835],"category_scores_gemma":[0.0008082526,0.0002442924,0.0002464027,0.0005517051,0.0003589102,0.0008187224,0.0002844816,0.0004858516,0.0008877715],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001181433,"about_ca_system_score_gemma":0.001083197,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007271484,"about_ca_topic_score_gemma":0.005326429,"domain_scores_codex":[0.999637,0.00007358821,0.00002818169,0.00005899832,0.00009661011,0.0001055979],"domain_scores_gemma":[0.9996684,0.00009183309,0.00004364021,0.00007552443,0.00008993509,0.00003076058],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.002093032,0.0004981053,0.007560832,0.0008057941,0.0001538748,0.0008384387,0.0004801016,0.2343539,0.08909151,0.05853629,0.02439485,0.5811933],"study_design_scores_gemma":[0.0003400948,0.0009346441,0.002247188,0.00009210875,0.0001020521,0.000494518,0.0001315569,0.8052794,0.1183478,0.01115703,0.06078437,0.00008936728],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1620893,0.0007842832,0.7910898,0.0003602057,0.0003287658,0.0003837454,0.0003253604,0.02107489,0.02356369],"genre_scores_gemma":[0.718164,0.0002548217,0.2751624,0.0001975119,0.00004687147,0.0001315429,0.0002222873,0.0001553743,0.005665235],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007271484,"threshold_uncertainty_score":0.01608378,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009371858419243793,"score_gpt":0.2326240732346361,"score_spread":0.2232522148153923,"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."}}