{"id":"W2042858188","doi":"10.1109/tnet.2011.2176140","title":"Optimal Control of Wireless Networks With Finite Buffers","year":2011,"lang":"en","type":"article","venue":"IEEE/ACM Transactions on Networking","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":49,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut National de la Recherche Scientifique; Université du Québec à Montréal","funders":"","keywords":"Computer science; Queue; Bounded function; Scheduling (production processes); Flow network; Notation; Algorithm; Theoretical computer science; Discrete mathematics; Computer network; Mathematics; Mathematical optimization; Arithmetic","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001226306,0.0003587567,0.0004149918,0.0001699527,0.0001544276,0.00001989119,0.0003107026,0.0001938001,0.00007180629],"category_scores_gemma":[0.000002136643,0.0003587981,0.000117278,0.0006342501,0.0001145763,0.0002286352,0.000002615394,0.0004889956,0.000006367924],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008220575,"about_ca_system_score_gemma":0.00001815413,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001135877,"about_ca_topic_score_gemma":0.00003431685,"domain_scores_codex":[0.998418,0.00005177837,0.0004380308,0.0003134194,0.0002291343,0.0005496099],"domain_scores_gemma":[0.9988415,0.000265502,0.0001212921,0.0005601624,0.00008257623,0.0001289406],"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":[0.0002433758,0.00005744205,0.000205896,0.0000240761,0.0001778992,0.00001030613,0.0002448711,0.9641876,0.00006457065,0.00002212007,0.00002158414,0.0347403],"study_design_scores_gemma":[0.001102261,0.0001891529,0.0001136788,0.0002527011,0.0001144341,0.00001009105,0.00005513386,0.9959681,0.001581281,0.00002847336,0.0001878794,0.0003967973],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01311317,0.0002624626,0.9838193,0.000007788772,0.001111943,0.0003432802,0.00001055401,0.0005081034,0.0008234045],"genre_scores_gemma":[0.9708313,0.0005039733,0.02810181,0.00004343188,0.0002659383,0.00007945193,0.000007588093,0.0001356168,0.00003090719],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9577181,"threshold_uncertainty_score":0.9998864,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01425126049083637,"score_gpt":0.1916679615832101,"score_spread":0.1774167010923738,"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."}}