{"id":"W4317793548","doi":"10.1109/honet56683.2022.10019191","title":"Sustainable and Secure Optimization of Load Distribution in Edge Computing","year":2022,"lang":"en","type":"article","venue":"","topic":"IoT and Edge/Fog Computing","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of New Brunswick","funders":"Natural Sciences and Engineering Research Council of Canada; Council of Independent Colleges","keywords":"Server; Computer science; Load balancing (electrical power); Cloud computing; Edge computing; Enhanced Data Rates for GSM Evolution; Distributed computing; Edge device; Computer network; Telecommunications; 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":[0.0004166514,0.0005708881,0.0004815964,0.0003209411,0.0004779803,0.0007838719,0.0004923766,0.0004600602,0.000744979],"category_scores_gemma":[0.0008271951,0.0002199362,0.0003661113,0.0003282026,0.0004011579,0.000733344,0.0005121556,0.0004155851,0.0001288458],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005561297,"about_ca_system_score_gemma":0.0005318857,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002330577,"about_ca_topic_score_gemma":0.00232971,"domain_scores_codex":[0.9997479,0.00007010818,0.00001033848,0.00004803929,0.00006406951,0.00005946895],"domain_scores_gemma":[0.999778,0.00009255299,0.00003894332,0.00002410522,0.00004328161,0.00002319127],"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":[0.0001046462,0.00006785768,0.001083027,0.00003703783,0.00003134876,0.00007580647,0.0000444365,0.9623739,0.007938074,0.005842946,0.0006135431,0.02178739],"study_design_scores_gemma":[0.000004394677,0.00002216491,0.0001726064,0.000001842559,0.000003536102,0.000008496025,0.00001269624,0.9973426,0.0008350582,0.00136795,0.0002261288,0.000002388285],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1446612,0.000355016,0.8480509,0.0002731986,0.00006651781,0.0000678154,0.00003673795,0.0002588569,0.00622984],"genre_scores_gemma":[0.9591448,0.0001325863,0.03954849,0.00005697971,0.00001177048,0.00002987202,0.00002334561,0.00003167445,0.001020459],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002330577,"threshold_uncertainty_score":0.004634082,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00622050254617157,"score_gpt":0.212171828035973,"score_spread":0.2059513254898015,"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."}}