{"id":"W1983574453","doi":"10.5555/982792.982947","title":"Optimally scheduling video-on-demand to minimize delay when server and receiver bandwidth may differ","year":2004,"lang":"en","type":"article","venue":"","topic":"Complexity and Algorithms in Graphs","field":"Computer Science","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Bandwidth (computing); Computer science; Network packet; Computer network; Upper and lower bounds; Scheduling (production processes); Bandwidth allocation; Real-time computing; Dynamic bandwidth allocation; Algorithm; Mathematics; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002548963,0.001551609,0.001767126,0.0005871204,0.0008729863,0.002159839,0.002212518,0.001552547,0.003114583],"category_scores_gemma":[0.01026792,0.0008737177,0.0002666266,0.0007490634,0.001243782,0.00271427,0.001598524,0.001499935,0.0004044759],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002744674,"about_ca_system_score_gemma":0.002341537,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00398767,"about_ca_topic_score_gemma":0.004324247,"domain_scores_codex":[0.9983743,0.0004665412,0.00009099676,0.0003012021,0.0002860849,0.0004807884],"domain_scores_gemma":[0.9931244,0.004292668,0.0006960907,0.0005912549,0.0006415622,0.0006540483],"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":[0.0006851258,0.0002852562,0.000942368,0.0001983206,0.00005367139,0.00007438328,0.0001281918,0.9178649,0.02808415,0.02226367,0.001966394,0.02745356],"study_design_scores_gemma":[0.00003067533,0.00008583114,0.0001267977,0.000005202117,0.000009842526,0.000009100739,0.00003358308,0.9922851,0.002419613,0.004672225,0.0003133844,0.000008493815],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2895828,0.0007047973,0.6994208,0.0009072898,0.0001638012,0.0003120996,0.0002369903,0.0005871651,0.008084214],"genre_scores_gemma":[0.9317135,0.0002419561,0.06577755,0.0001219404,0.00006098025,0.0001280809,0.0001188548,0.0001718557,0.001665251],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00398767,"threshold_uncertainty_score":0.01991409,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02072290224461794,"score_gpt":0.2438851805099548,"score_spread":0.2231622782653368,"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."}}