{"id":"W2983694339","doi":"10.1109/tmc.2019.2953163","title":"Software-Defined Cooperative Data Sharing in Edge Computing Assisted 5G-VANET","year":2019,"lang":"en","type":"article","venue":"IEEE Transactions on Mobile Computing","topic":"Vehicular Ad Hoc Networks (VANETs)","field":"Engineering","cited_by":149,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Science Foundation of Beijing Municipality; Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China","keywords":"Computer science; Vehicular ad hoc network; Computer network; Distributed computing; Mobile edge computing; Data sharing; Software-defined networking; Edge computing; Dedicated short-range communications; Wireless ad hoc network; Cloud computing; Server; Wireless; Operating system","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":[0.0008081467,0.0006726861,0.0008203929,0.0005247323,0.0007504026,0.001137414,0.001590274,0.0005553418,0.001124095],"category_scores_gemma":[0.001372934,0.000266654,0.0005010587,0.001025227,0.000680853,0.001158952,0.001472886,0.0005844178,0.000183369],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009528321,"about_ca_system_score_gemma":0.001405388,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00485403,"about_ca_topic_score_gemma":0.004383475,"domain_scores_codex":[0.9988822,0.0002842792,0.000053541,0.0002652337,0.0002710198,0.0002436987],"domain_scores_gemma":[0.9993975,0.000221101,0.0000872128,0.00008071152,0.0001470369,0.00006646231],"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":[0.000145684,0.00007214331,0.0005262644,0.00007595402,0.00004035115,0.0002227241,0.0001404224,0.9054403,0.006768262,0.03382825,0.001637944,0.05110167],"study_design_scores_gemma":[0.00000751785,0.00003588988,0.00005298013,0.000003335647,0.000005746172,0.00003538596,0.00003442091,0.9925699,0.0009304942,0.005510762,0.0008070873,0.000006505499],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03477049,0.0002482408,0.9608123,0.0001797437,0.00005991504,0.00007315986,0.00005241545,0.0001940975,0.003609654],"genre_scores_gemma":[0.8951538,0.0002084761,0.1021953,0.0001223092,0.00003067267,0.0001377679,0.000120622,0.00002950693,0.002001702],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00485403,"threshold_uncertainty_score":0.009651542,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02471518104194979,"score_gpt":0.2561665114549453,"score_spread":0.2314513304129955,"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."}}