{"id":"W2089968732","doi":"10.5555/1554126.1554144","title":"Multi-objective scheduling for MUD based ad-hoc networks","year":2008,"lang":"en","type":"article","venue":"International Wireless Internet Conference","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Computer science; Maximum throughput scheduling; Scheduling (production processes); Quality of service; Distributed computing; Round-robin scheduling; Computer network; Proportionally fair; Fair-share scheduling; Dynamic priority scheduling; Throughput; Job shop scheduling; Queueing theory; Wireless ad hoc network; Mathematical optimization; Wireless","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":[0.00009282894,0.0003230866,0.0002848462,0.0001679105,0.00007959193,0.00006773059,0.0005494138,0.0001726843,0.0001777336],"category_scores_gemma":[0.00007038888,0.0003633311,0.000128707,0.0001526616,0.0001189261,0.0003417078,0.00006445513,0.0003117296,0.00003162975],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002525258,"about_ca_system_score_gemma":0.0000576302,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005902185,"about_ca_topic_score_gemma":0.00005262111,"domain_scores_codex":[0.9984734,0.00002580127,0.0004375382,0.0004189365,0.0002593427,0.0003849657],"domain_scores_gemma":[0.9988316,0.0002178527,0.0001198172,0.0002285928,0.0004942513,0.0001079091],"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":[0.0001023401,0.00005504971,0.0006497787,0.00001912297,0.0001050523,0.00001371104,0.0002405115,0.9816064,0.0007330215,0.0009730957,0.0003930737,0.01510885],"study_design_scores_gemma":[0.001146458,0.0000457663,0.0006214511,0.0001675229,0.0000105395,0.00001575286,0.00003930309,0.9910189,0.003318652,0.0000672523,0.003166134,0.0003822819],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05963063,0.0004093023,0.9364105,0.0000633234,0.001788364,0.0003654439,0.00003817156,0.0004989189,0.0007953103],"genre_scores_gemma":[0.9108,0.0004945322,0.08714425,0.0001272261,0.0002516484,0.0002289615,0.000190828,0.00008473702,0.0006777719],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8511694,"threshold_uncertainty_score":0.9998819,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02700086746876842,"score_gpt":0.2563230581023253,"score_spread":0.2293221906335568,"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."}}