{"id":"W3110974438","doi":"10.1145/3444692","title":"A Survey on Edge Performance Benchmarking","year":2021,"lang":"en","type":"review","venue":"ACM Computing Surveys","topic":"IoT and Edge/Fog Computing","field":"Computer Science","cited_by":78,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"National Research Foundation of Korea; Royal Society","keywords":"Benchmarking; Computer science; Software deployment; Benchmark (surveying); Orchestration; Leverage (statistics); Data science; Context (archaeology); The Internet; Edge computing; Resource (disambiguation); Enhanced Data Rates for GSM Evolution; Distributed computing; World Wide Web; Software engineering; Telecommunications; Artificial intelligence","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":[0.003473383,0.001350788,0.001370909,0.007779314,0.0006519066,0.00332252,0.002257941,0.001572946,0.008534973],"category_scores_gemma":[0.01265063,0.0006618523,0.0007757756,0.01441457,0.000620166,0.005980959,0.0014691,0.001562343,0.005708572],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001442362,"about_ca_system_score_gemma":0.002872183,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002486129,"about_ca_topic_score_gemma":0.002397674,"domain_scores_codex":[0.9970143,0.0005371263,0.0002620759,0.0003520891,0.001576613,0.0002578694],"domain_scores_gemma":[0.989461,0.005659776,0.0005842815,0.0004081933,0.003573655,0.0003130658],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00006419203,0.00009202954,0.001385326,0.009924429,0.0000563699,0.0000778502,0.0001154373,0.00170743,0.0007032834,0.01928391,0.08751507,0.8790747],"study_design_scores_gemma":[0.000008454758,0.0001312948,0.001754508,0.008500062,0.00007753468,0.0003250771,0.0002022342,0.001201859,0.000855629,0.006114062,0.9807802,0.00004906564],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.001153513,0.9693485,0.004960747,0.002250922,0.001278504,0.00005988116,0.000287054,0.000231999,0.02042894],"genre_scores_gemma":[0.00794051,0.9817346,0.00359545,0.001197384,0.001333007,0.00006444871,0.0006426467,0.0001101682,0.00338172],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.008534973,"threshold_uncertainty_score":0.02855229,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1161239236735101,"score_gpt":0.3416418763134337,"score_spread":0.2255179526399236,"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."}}