{"id":"W2026453648","doi":"10.1109/infcom.2013.6566873","title":"Joint request mapping and response routing for geo-distributed cloud services","year":2013,"lang":"en","type":"article","venue":"","topic":"Software-Defined Networks and 5G","field":"Computer Science","cited_by":171,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Cloud computing; Workload; Distributed computing; Latency (audio); Reliability (semiconductor); Server; Routing (electronic design automation); Bandwidth (computing); Optimization problem; Mathematical optimization; Computer network; Algorithm","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":[0.001684294,0.0007981844,0.0007507149,0.0005972511,0.001009379,0.001053943,0.001064372,0.001032821,0.001478767],"category_scores_gemma":[0.003165684,0.0004466775,0.0003914916,0.001004834,0.0007464429,0.001416463,0.001007654,0.0007376088,0.0003642919],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001181931,"about_ca_system_score_gemma":0.002059173,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00612366,"about_ca_topic_score_gemma":0.008325608,"domain_scores_codex":[0.9990332,0.0004839927,0.00003593313,0.0001837499,0.0001589536,0.0001041378],"domain_scores_gemma":[0.9987592,0.0006076825,0.0001830891,0.0002074703,0.0001405409,0.0001021298],"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":[0.0001146649,0.00009156754,0.0007170204,0.00005885016,0.0000233645,0.0000800643,0.000106863,0.90635,0.003902371,0.01124157,0.002431828,0.07488196],"study_design_scores_gemma":[0.000008935025,0.00001497976,0.00009650776,0.000001859317,0.00000272824,0.00001896928,0.0000308698,0.9938058,0.0006679738,0.004726966,0.0006203356,0.000004129313],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02882624,0.0002120268,0.9677641,0.000444793,0.00004249563,0.00007142774,0.00004576697,0.0006858048,0.001907406],"genre_scores_gemma":[0.6537599,0.0001688691,0.3432787,0.000114176,0.00006195407,0.0001160683,0.0001561496,0.0001168785,0.002227265],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00612366,"threshold_uncertainty_score":0.01217604,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02057981216604238,"score_gpt":0.2227100585970537,"score_spread":0.2021302464310114,"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."}}