{"id":"W2521027152","doi":"10.1109/spin.2016.7566742","title":"Admission control and power allocation for energy harvesting systems with QoS provisioning","year":2016,"lang":"en","type":"article","venue":"","topic":"Energy Harvesting in Wireless Networks","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Quality of service; Provisioning; Resource allocation; Scheme (mathematics); Admission control; Computer network; Distributed computing; Resource management (computing); Power control; Call Admission Control; Control (management); Dynamic programming; Energy (signal processing); Power (physics); Mathematical optimization; Wireless; Wireless network; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001898117,0.0009223028,0.001266797,0.000424585,0.001019201,0.001848821,0.001676429,0.001165917,0.002079582],"category_scores_gemma":[0.005250243,0.0004454631,0.0005079831,0.0005889553,0.001420858,0.001733507,0.001701394,0.00216126,0.0002653833],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001556756,"about_ca_system_score_gemma":0.001834692,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003377638,"about_ca_topic_score_gemma":0.002079538,"domain_scores_codex":[0.9979718,0.0006874226,0.0001104502,0.000394763,0.0004855293,0.0003501031],"domain_scores_gemma":[0.9970943,0.001997677,0.0003012537,0.0001844987,0.0002601282,0.0001622966],"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":[0.0002270723,0.0001746199,0.0006757987,0.0001078558,0.00005541171,0.0001941856,0.0003195339,0.8445089,0.007571782,0.0719476,0.001607211,0.07260992],"study_design_scores_gemma":[0.00001100164,0.00001298181,0.00004964993,0.000003366928,0.000004364848,0.00001657281,0.00001519429,0.989077,0.0004908383,0.01000291,0.0003095049,0.000006613649],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0140384,0.0002451471,0.9829474,0.0003486363,0.00007037963,0.00006202292,0.00001475685,0.0001676878,0.002105507],"genre_scores_gemma":[0.9456449,0.0002618759,0.05076919,0.0001515432,0.0001716658,0.0001336901,0.00003238663,0.00003492568,0.002799753],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003377638,"threshold_uncertainty_score":0.01129508,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005045539998031368,"score_gpt":0.1811317779685886,"score_spread":0.1760862379705572,"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."}}