{"id":"W4402389137","doi":"10.1109/jiot.2024.3456846","title":"Joint Optimization of Caching, Computing, and Trajectory Planning in Aerial Mobile Edge Computing Networks: An MADDPG Approach","year":2024,"lang":"en","type":"article","venue":"IEEE Internet of Things Journal","topic":"UAV Applications and Optimization","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"National Natural Science Foundation of China","keywords":"Computer science; Mobile edge computing; Joint (building); Edge computing; Trajectory; Mobile computing; Mobile telephony; Distributed computing; Enhanced Data Rates for GSM Evolution; Trajectory optimization; Computer network; Server; Mobile radio; Artificial intelligence","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":[0.001004044,0.001099002,0.001409331,0.0004351485,0.0005188789,0.001135508,0.00137033,0.001274668,0.001965323],"category_scores_gemma":[0.002447702,0.0005664212,0.0005446217,0.0006558719,0.0009531506,0.001014424,0.001165402,0.00129668,0.0002204838],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001727377,"about_ca_system_score_gemma":0.002024926,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01659288,"about_ca_topic_score_gemma":0.01489587,"domain_scores_codex":[0.9995096,0.0001439077,0.00001868793,0.0001147075,0.00007804777,0.0001350667],"domain_scores_gemma":[0.9990233,0.0006004987,0.00009221162,0.00006259864,0.0001247109,0.0000967452],"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":[0.00003024559,0.00001799169,0.000300477,0.00001934255,0.00001357796,0.00003430048,0.00001677747,0.988831,0.0002219158,0.003668825,0.0004742071,0.006371267],"study_design_scores_gemma":[0.000002656308,0.000006888698,0.00002701003,0.000001357823,0.000002046821,0.000003250954,0.000004354857,0.9984718,0.00005009233,0.001334267,0.00009527064,0.000001053161],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04494066,0.0007159812,0.9486831,0.0007826944,0.0001136601,0.00007618477,0.0001457147,0.0004088623,0.004133143],"genre_scores_gemma":[0.9021878,0.000261943,0.09344172,0.0003102498,0.00005539568,0.0001160681,0.0001669557,0.0001056596,0.003354256],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01659288,"threshold_uncertainty_score":0.0329926,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01249696768297399,"score_gpt":0.2431872979919029,"score_spread":0.2306903303089289,"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."}}