{"id":"W3127503959","doi":"10.1016/j.comnet.2021.107904","title":"Stochastic joint rate control and resource allocation for wireless video surveillance","year":2021,"lang":"en","type":"article","venue":"Computer Networks","topic":"Advanced Wireless Network Optimization","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"Memorial University of Newfoundland","funders":"Newfoundland and Labrador; Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China","keywords":"Computer science; Base station; Telecommunications link; Resource allocation; Lyapunov optimization; Wireless; Real-time computing; Upload; Latency (audio); Quality of service; Optimization problem; Mathematical optimization; Computer network; Algorithm; Telecommunications; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":true,"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":[],"consensus_categories":[],"category_scores_codex":[0.000167657,0.000173153,0.0002584261,0.00003106565,0.00008416161,0.00006821407,0.00007016469,0.00009731382,0.000002570797],"category_scores_gemma":[0.00001292549,0.000199011,0.0000408507,0.000165499,0.00002863829,0.00009270787,0.00003660791,0.0001331183,0.000001440315],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004890745,"about_ca_system_score_gemma":0.00001041459,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":4.060051e-7,"about_ca_topic_score_gemma":0.000007423147,"domain_scores_codex":[0.9990716,0.0000590888,0.0002462332,0.0002744785,0.00006381514,0.0002847618],"domain_scores_gemma":[0.9992858,0.0002511783,0.00005161598,0.0002234896,0.0001104604,0.00007748324],"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":[0.00001176621,0.000006165247,0.0000303559,0.00003105239,0.00003275543,0.00000267107,0.0000299632,0.958784,0.0001060914,0.000313494,0.002200093,0.03845154],"study_design_scores_gemma":[0.0008619262,0.00001959825,0.001048172,0.00006870525,0.00001099257,0.00000943626,0.000004175911,0.9965634,0.00003388772,0.0001169112,0.001051656,0.0002111717],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.004663373,0.001653959,0.9923812,0.0001260335,0.0005595291,0.0003029388,0.000005169249,0.0002774707,0.00003037964],"genre_scores_gemma":[0.9827256,0.0001386891,0.01574202,0.0002628354,0.0008659234,0.00006103569,0.0001139235,0.00006024368,0.00002975438],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9780622,"threshold_uncertainty_score":0.8115433,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00652270278845727,"score_gpt":0.1886852197313295,"score_spread":0.1821625169428722,"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."}}