{"id":"W2773419383","doi":"10.1109/iemcon.2017.8117206","title":"Dynamic load balancing in SDN-based data center networks","year":2017,"lang":"en","type":"article","venue":"","topic":"Software-Defined Networks and 5G","field":"Computer Science","cited_by":49,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Computer science; Load balancing (electrical power); Software-defined networking; Data center; Computer network; Cloud computing; Distributed computing; Load management; Network packet; Bandwidth (computing); Packet loss; Throughput; Wireless; Grid","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":[],"consensus_categories":[],"category_scores_codex":[0.0004532275,0.0001321505,0.0001595638,0.00004213496,0.0001999655,0.0004853507,0.003472331,0.00007454101,0.00002982837],"category_scores_gemma":[0.00008238813,0.0001126757,0.0000314596,0.0001045027,0.00003760809,0.0006791467,0.001174128,0.0001801347,0.00004371173],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006314537,"about_ca_system_score_gemma":0.00008543092,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003535549,"about_ca_topic_score_gemma":0.001869539,"domain_scores_codex":[0.9986404,0.0000292296,0.0001924237,0.0005318056,0.0002073825,0.000398775],"domain_scores_gemma":[0.9964877,0.0001054887,0.000096744,0.003199111,0.00003219636,0.00007878988],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00003676495,0.0003113561,0.5577691,0.00002938499,0.00003158345,0.0002633595,0.0001216972,0.04710469,0.00001880078,0.00568042,0.03657057,0.3520622],"study_design_scores_gemma":[0.0005547357,0.00001303406,0.06307839,0.00004902011,0.00000143817,0.000002972257,0.000001513235,0.9331542,0.000002734004,0.0002060011,0.002791603,0.0001443156],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.005066362,0.0001696042,0.9884208,0.001459907,0.0008752341,0.0001100368,0.000004145156,0.000183824,0.003710053],"genre_scores_gemma":[0.96935,0.000020039,0.02919011,0.001106694,0.00006811289,0.000004298779,0.00002082894,0.00001010529,0.0002298401],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9642836,"threshold_uncertainty_score":0.6452513,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02501504582800795,"score_gpt":0.2748085066261555,"score_spread":0.2497934607981475,"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."}}