{"id":"W3039417973","doi":"10.1109/vtc2020-spring48590.2020.9128850","title":"Association and Scheduling in Energy Harvesting Networks: Age of Information and Fairness Trade-off","year":2020,"lang":"en","type":"article","venue":"","topic":"Age of Information Optimization","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Montréal","funders":"","keywords":"Knapsack problem; Network packet; Computer science; Scheduling (production processes); Fairness measure; Mathematical optimization; Dynamic programming; Job shop scheduling; Dynamic priority scheduling; Efficient energy use; Distributed computing; Computer network; Wireless; Algorithm; Throughput; Mathematics; Quality of service; Routing (electronic design automation)","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":[0.004033131,0.001047284,0.00174023,0.000738519,0.001080501,0.001697223,0.001735607,0.001474208,0.001513546],"category_scores_gemma":[0.008811772,0.0005847009,0.0004566142,0.001512603,0.001098142,0.003154624,0.001607541,0.001173058,0.0002367637],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001614288,"about_ca_system_score_gemma":0.001533826,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001494941,"about_ca_topic_score_gemma":0.001376845,"domain_scores_codex":[0.998284,0.0006223829,0.00008364041,0.0003825122,0.00032378,0.0003035251],"domain_scores_gemma":[0.9933828,0.005004989,0.0006433927,0.0003140457,0.0003533545,0.0003014792],"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":[0.0003779685,0.0001992733,0.002035561,0.0001793111,0.00006917221,0.0001992341,0.0002047743,0.8684419,0.005094773,0.05126879,0.001187516,0.07074168],"study_design_scores_gemma":[0.00002118363,0.0001219208,0.0004858905,0.000016542,0.00002395238,0.0001384484,0.00005993176,0.9630687,0.001942753,0.03275416,0.00134641,0.00002003018],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.067302,0.001963533,0.9264482,0.0005103309,0.0001327972,0.00007492286,0.00006774109,0.00009578204,0.003404707],"genre_scores_gemma":[0.8959275,0.001370602,0.09796862,0.0001443682,0.0002473608,0.00008881086,0.00005030195,0.00006306137,0.004139389],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004033131,"threshold_uncertainty_score":0.02132952,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008501479887760743,"score_gpt":0.1914711873897655,"score_spread":0.1829697075020048,"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."}}