{"id":"W4405179167","doi":"10.1109/tgcn.2024.3514578","title":"EMDTORA: Energy-Aware Multi-User Dependent Task Offloading and Resource Allocation in MEC Using Graph-Enabled DRL","year":2024,"lang":"en","type":"article","venue":"IEEE Transactions on Green Communications and Networking","topic":"IoT and Edge/Fog Computing","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Graph; Task (project management); Resource allocation; Distributed computing; Human–computer interaction; Computer network; Theoretical computer science; Engineering; Systems engineering","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005075266,0.0002066551,0.0001961635,0.0004498635,0.0008628631,0.0004078612,0.0006119921,0.0001140625,8.257766e-7],"category_scores_gemma":[4.792e-7,0.000218265,0.00006213041,0.0009359127,0.00008353678,0.0004643726,0.00005681063,0.0004399723,0.000001693844],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001069571,"about_ca_system_score_gemma":0.00005446385,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001463408,"about_ca_topic_score_gemma":0.001019387,"domain_scores_codex":[0.9984788,0.0002193875,0.0003652921,0.0004476167,0.0001625691,0.0003262857],"domain_scores_gemma":[0.9986041,0.0003491873,0.00006993212,0.0008357685,0.00004702419,0.00009401557],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000009159287,0.0001141246,0.0002156419,0.00004589984,0.00007279129,0.00001047624,0.00226279,0.002008088,0.0008979389,0.0005859467,0.00007803332,0.9936991],"study_design_scores_gemma":[0.0002648724,0.00002855405,0.00004604719,0.0004530917,0.00003166069,0.00003572908,0.00007253266,0.9822062,0.0001810951,0.0003223044,0.01611637,0.0002415363],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.006644614,0.004493982,0.9865686,0.000676627,0.001135167,0.0001458846,0.000001002512,0.0001980717,0.0001360608],"genre_scores_gemma":[0.9848178,0.001291646,0.01324683,0.0001562285,0.0002096303,0.00002851181,0.00000401098,0.00002632455,0.0002190122],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9934576,"threshold_uncertainty_score":0.8900589,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03970154792415301,"score_gpt":0.2686039753289005,"score_spread":0.2289024274047475,"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."}}