{"id":"W2791851645","doi":"10.1109/tc.2018.2818144","title":"Cloudlets Activation Scheme for Scalable Mobile Edge Computing with Transmission Power Control and Virtual Machine Migration","year":2018,"lang":"en","type":"article","venue":"IEEE Transactions on Computers","topic":"IoT and Edge/Fog Computing","field":"Computer Science","cited_by":178,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"National Institute of Information and Communications Technology; Ministerio de Economía y Competitividad","keywords":"Computer science; Scalability; Scheme (mathematics); Mobile edge computing; Enhanced Data Rates for GSM Evolution; Transmission (telecommunications); Mobile computing; Distributed computing; Power control; Power (physics); Computer network; Computer architecture; Operating system; Telecommunications","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0002945212,0.0002912848,0.0002728011,0.0002299517,0.0007770033,0.0002387393,0.0003351318,0.0001127613,0.000003112264],"category_scores_gemma":[0.000002394539,0.0002579151,0.00009320866,0.00039843,0.0001142067,0.0005498697,0.000005254293,0.0002256536,0.0000110759],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007512587,"about_ca_system_score_gemma":0.00006691131,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003056327,"about_ca_topic_score_gemma":0.000004912579,"domain_scores_codex":[0.998303,0.00006660448,0.0003191146,0.0006191024,0.000271207,0.0004209701],"domain_scores_gemma":[0.9988397,0.0003441888,0.0001259685,0.0003273791,0.0002030956,0.0001596252],"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":[0.000811702,0.0006700448,0.0001035405,0.00007855509,0.0002319772,0.00000587256,0.00648095,0.03428686,0.03434829,0.0003076924,0.003281578,0.9193929],"study_design_scores_gemma":[0.002437388,0.002029208,0.0001823786,0.0001743346,0.00002045596,0.0000260479,0.0000267618,0.9617834,0.02911941,0.00004122365,0.003798809,0.000360584],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1349355,0.00001838067,0.8608317,0.0004318498,0.002838024,0.0006187276,0.000002033167,0.000282179,0.00004161783],"genre_scores_gemma":[0.9092549,0.000003379868,0.08967322,0.0005275127,0.0004454412,0.00001977047,0.000003875254,0.00002684526,0.00004503299],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9274966,"threshold_uncertainty_score":0.9999873,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00834257827932496,"score_gpt":0.2281554552691704,"score_spread":0.2198128769898454,"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."}}