{"id":"W1979865356","doi":"10.1002/nem.421","title":"An adaptive load balancing scheme for web servers","year":2002,"lang":"en","type":"article","venue":"International Journal of Network Management","topic":"Network Traffic and Congestion Control","field":"Computer Science","cited_by":72,"is_retracted":false,"has_abstract":true,"ca_institutions":"Nortel (Canada)","funders":"","keywords":"Computer science; Server; Round-robin DNS; Web server; Scheme (mathematics); Load balancing (electrical power); Computer network; Client–server model; Process (computing); Control (management); Distributed computing; World Wide Web; Operating system; The Internet; 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":[0.0007827015,0.000462141,0.0004711993,0.0009170548,0.0009581604,0.001051324,0.00140477,0.0006155015,0.003347598],"category_scores_gemma":[0.001752193,0.0002062952,0.0001980082,0.0006892298,0.0005193863,0.00132336,0.001380296,0.0009106945,0.0009046661],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006674557,"about_ca_system_score_gemma":0.0004191184,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009103406,"about_ca_topic_score_gemma":0.0007107435,"domain_scores_codex":[0.9991915,0.0001929818,0.00005498957,0.0001304726,0.0003162241,0.0001137678],"domain_scores_gemma":[0.9990414,0.000195661,0.00008187497,0.0002433652,0.0002957775,0.0001418673],"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":[0.001730382,0.0009686589,0.002755559,0.0002015666,0.0001086479,0.0005031091,0.0006260732,0.1573933,0.1996702,0.05458118,0.01073806,0.5707232],"study_design_scores_gemma":[0.0001630348,0.0001658899,0.0008495837,0.00001598948,0.00003419286,0.0001634698,0.00004630576,0.9425068,0.02637154,0.01759579,0.01203883,0.00004851312],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1454752,0.0005429812,0.8351462,0.0004114601,0.0002619108,0.0002690142,0.00009658473,0.00721064,0.01058601],"genre_scores_gemma":[0.9323398,0.0001267047,0.06226232,0.0001632859,0.0001426641,0.0001191955,0.0001077027,0.0001314118,0.004606883],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003347598,"threshold_uncertainty_score":0.01119888,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01618493320392848,"score_gpt":0.2421719836117736,"score_spread":0.2259870504078451,"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."}}