{"id":"W2113831551","doi":"10.1109/icdcs.2005.30","title":"End-to-End Fair Bandwidth Allocation in Multi-Hop Wireless Ad Hoc Networks","year":2005,"lang":"en","type":"article","venue":"","topic":"Wireless Networks and Protocols","field":"Computer Science","cited_by":62,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Computer network; Wireless ad hoc network; Maximum throughput scheduling; Hop (telecommunications); Reuse; End-to-end principle; Scheduling (production processes); Fairness measure; Wireless; Bandwidth (computing); Bandwidth allocation; Wireless network; Distributed computing; Throughput; Dynamic priority scheduling; Quality of service; Round-robin scheduling; Telecommunications; Engineering","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":[0.00565612,0.0006827085,0.0007466293,0.0007516057,0.001518301,0.001628391,0.001941022,0.001108299,0.0009171662],"category_scores_gemma":[0.009847187,0.0003603426,0.0003239123,0.0006129824,0.001671356,0.002400359,0.001206512,0.0007413303,0.0002385497],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001460268,"about_ca_system_score_gemma":0.001496601,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002113027,"about_ca_topic_score_gemma":0.002193888,"domain_scores_codex":[0.9971999,0.001238331,0.000112915,0.0002406849,0.0009579679,0.00025014],"domain_scores_gemma":[0.9956903,0.002808308,0.0002082178,0.0005952229,0.0005794141,0.0001184755],"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":[0.0004708034,0.0002019054,0.001760983,0.0001354921,0.00005994459,0.0002469614,0.0002296303,0.7920071,0.007148779,0.08216134,0.001676841,0.1139002],"study_design_scores_gemma":[0.00003353966,0.00005875064,0.000204029,0.000009216715,0.00001588713,0.0000535581,0.00002824732,0.966116,0.003411393,0.02832149,0.001735215,0.00001276977],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03104315,0.0006796898,0.9647048,0.0001795034,0.0001087055,0.0001074153,0.0000210229,0.0003571381,0.002798557],"genre_scores_gemma":[0.7992325,0.0005583778,0.1965425,0.0001019578,0.0001124655,0.0002573309,0.00005612576,0.00005808028,0.003080723],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00565612,"threshold_uncertainty_score":0.02991277,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02246923897096811,"score_gpt":0.2739504298465881,"score_spread":0.25148119087562,"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."}}