{"id":"W2911523720","doi":"10.3166/isi.23.6.87-98","title":"Dynamic load balancing for client server assignment in distributed system using genetical gorithm","year":2018,"lang":"en","type":"article","venue":"Ingénierie des systèmes d information","topic":"Distributed and Parallel Computing Systems","field":"Computer Science","cited_by":22,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Computer science; Client–server model; Load balancing (electrical power); Distributed computing; Round-robin DNS; Operating system; Computer network; Server; The Internet; Mathematics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"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":[0.001093956,0.0002219017,0.0002965197,0.000159714,0.0002883338,0.0004989828,0.0005265575,0.0001368392,0.000002682656],"category_scores_gemma":[0.00009452251,0.0002165719,0.00008517459,0.0005052018,0.00007499288,0.001347158,0.000180853,0.00009946365,0.00006858899],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001944323,"about_ca_system_score_gemma":0.0002126108,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001170401,"about_ca_topic_score_gemma":0.00002834756,"domain_scores_codex":[0.9977753,0.0001037509,0.0008835499,0.0002633007,0.0004408465,0.000533293],"domain_scores_gemma":[0.9985846,0.00007955372,0.0003386318,0.000417143,0.0004688851,0.0001112415],"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":[0.0004256257,0.0006001538,0.02840359,0.009654994,0.0005067694,0.00007300051,0.0565187,0.511077,0.002124473,0.2088448,0.003452438,0.1783184],"study_design_scores_gemma":[0.0006500705,0.0001122266,0.003754867,0.0004755753,0.000008243547,0.00005500949,0.0004425828,0.991992,0.0001692698,0.0004183242,0.001657365,0.0002644684],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1746359,0.00003736937,0.8231446,0.00002797601,0.0009220546,0.0005177356,0.00005695388,0.0002044118,0.0004530328],"genre_scores_gemma":[0.9736049,7.014158e-7,0.026094,0.00004586034,0.00008820368,0.0000353365,0.0001121106,0.000009052925,0.000009804464],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.798969,"threshold_uncertainty_score":0.8831547,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01498050369027105,"score_gpt":0.2493445441899992,"score_spread":0.2343640404997282,"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."}}