{"id":"W4252790325","doi":"10.1109/eco-friendly.2014.91","title":"Green Wireless Access Virtualization Implementation: Cost vs. QoS Trade-offs","year":2014,"lang":"en","type":"article","venue":"","topic":"Software-Defined Networks and 5G","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut National de la Recherche Scientifique; École de Technologie Supérieure; Prompt (Canada); Université du Québec à Montréal","funders":"","keywords":"Computer science; Computer network; Quality of service; Network virtualization; Virtualization; Provisioning; Wireless network; Operating expense; Capital expenditure; Wireless; Telecommunications; Cloud computing","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":[0.002167455,0.0007108357,0.0005530493,0.0006810815,0.0004660824,0.002495086,0.001122853,0.0006250991,0.002044672],"category_scores_gemma":[0.007494518,0.0002441713,0.0003650711,0.0006076414,0.0004951998,0.003025205,0.001036345,0.000747041,0.0001632521],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00162037,"about_ca_system_score_gemma":0.0009111727,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001432178,"about_ca_topic_score_gemma":0.002295518,"domain_scores_codex":[0.9980249,0.000660003,0.00005616358,0.0001217056,0.0006518943,0.000485307],"domain_scores_gemma":[0.9971488,0.001587639,0.0002160107,0.0002828458,0.0005725411,0.0001920973],"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":[0.000761806,0.0004683092,0.006921359,0.0002872784,0.0001249493,0.0004161774,0.0002742183,0.6108423,0.03581756,0.1232647,0.002303049,0.2185184],"study_design_scores_gemma":[0.00002274838,0.0003202477,0.00255856,0.00004035554,0.0000726133,0.0001501866,0.0002320963,0.9681438,0.01151415,0.01444658,0.002467314,0.00003133931],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6584791,0.002060691,0.2883175,0.002060548,0.0002007755,0.0001934255,0.00009547155,0.0005233249,0.04806907],"genre_scores_gemma":[0.9867991,0.0001694673,0.01217491,0.00002955846,0.00001297155,0.00001487179,0.00001268593,0.00002701128,0.0007593993],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002495086,"threshold_uncertainty_score":0.01175666,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02509435943157433,"score_gpt":0.2994217216117758,"score_spread":0.2743273621802014,"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."}}