{"id":"W1967033012","doi":"10.1145/1868521.1868559","title":"Optimal control to improve throughput, energy consumption and fairness in wireless networks","year":2010,"lang":"en","type":"article","venue":"","topic":"Wireless Networks and Protocols","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Maximum throughput scheduling; Throughput; Computer science; Computer network; Network packet; Fairness measure; Wireless network; Power control; Packet loss; Wireless; Energy consumption; Control (management); Resource (disambiguation); Resource allocation; Distributed computing; Power (physics); Quality of service; Telecommunications; Dynamic priority scheduling; 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":[0.001844685,0.000615251,0.0005292305,0.0003889146,0.0004603765,0.0007293188,0.0006851446,0.0003373313,0.0007280997],"category_scores_gemma":[0.003577631,0.0002260379,0.0002011622,0.000399873,0.001113333,0.000900789,0.0006550034,0.0005011793,0.00007382617],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001026957,"about_ca_system_score_gemma":0.001526063,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005716359,"about_ca_topic_score_gemma":0.004354226,"domain_scores_codex":[0.9991111,0.0002786933,0.00004634861,0.0001162159,0.0002999173,0.0001477303],"domain_scores_gemma":[0.9990156,0.0005821881,0.0001324581,0.00007111928,0.0001555779,0.00004318995],"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":[0.00009871198,0.0001172754,0.0004609214,0.00004385923,0.00002292424,0.00003108439,0.00005630777,0.9303899,0.006189194,0.02543643,0.000656648,0.03649683],"study_design_scores_gemma":[0.00001606472,0.000041393,0.0001266611,0.000002145055,0.000006857705,0.000007068108,0.000006066719,0.9912636,0.001255068,0.006954949,0.0003151283,0.000004886941],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06792086,0.0006274137,0.9272411,0.0002197587,0.00007632536,0.00004987414,0.00002029639,0.0004039784,0.003440364],"genre_scores_gemma":[0.9654241,0.0001704719,0.03347586,0.00004278563,0.00003040032,0.00003466162,0.00001145634,0.00001862983,0.0007916252],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005716359,"threshold_uncertainty_score":0.01136619,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006683683781992473,"score_gpt":0.2370776399906832,"score_spread":0.2303939562086907,"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."}}