{"id":"W4407783213","doi":"10.1109/ispa63168.2024.00110","title":"Dependency-aware Task Offloading and Resource Pricing in Vehicular Edge Computing: A Stackelberg Game Approach","year":2024,"lang":"en","type":"article","venue":"","topic":"Transportation and Mobility Innovations","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Stackelberg competition; Computer science; Dependency (UML); Task (project management); Enhanced Data Rates for GSM Evolution; Game theory; Resource management (computing); Edge computing; Resource (disambiguation); Distributed computing; Computer network; Artificial intelligence; Microeconomics; Economics","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":[0.001488016,0.001449402,0.001268744,0.0007191135,0.0009801063,0.001538659,0.002001446,0.001450292,0.001809909],"category_scores_gemma":[0.002210921,0.0004897292,0.0008682221,0.0007214748,0.001391021,0.001896158,0.001647853,0.001484789,0.0001530627],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002118546,"about_ca_system_score_gemma":0.003278678,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01218565,"about_ca_topic_score_gemma":0.01024467,"domain_scores_codex":[0.9989242,0.0003765197,0.00003448217,0.0001673725,0.0001712948,0.00032614],"domain_scores_gemma":[0.9992357,0.0003990542,0.00007976605,0.00003634019,0.0001155498,0.0001334814],"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":[0.00008605077,0.00007651537,0.0005498016,0.00004512582,0.00004070771,0.000153476,0.00008107123,0.9526953,0.001625658,0.03234871,0.000810795,0.01148684],"study_design_scores_gemma":[0.000007932975,0.0000279673,0.00005440917,0.000002739153,0.0000090572,0.00001722788,0.00002244744,0.9917805,0.0002303529,0.007580982,0.0002599338,0.000006443597],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05562317,0.0002915883,0.9372918,0.0004885472,0.00008705994,0.0001453673,0.00006973216,0.0001104225,0.005892333],"genre_scores_gemma":[0.943956,0.0003208698,0.05268201,0.000139362,0.0000377509,0.0001133516,0.00004351808,0.0000282749,0.002679012],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01218565,"threshold_uncertainty_score":0.02422941,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009605567641186087,"score_gpt":0.218953289093893,"score_spread":0.2093477214527069,"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."}}