{"id":"W2910025538","doi":"10.1109/access.2018.2889943","title":"Software Defined Network-Based Edge Cloud Resource Allocation Framework","year":2019,"lang":"en","type":"article","venue":"IEEE Access","topic":"Software-Defined Networks and 5G","field":"Computer Science","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Cloud computing; Computer science; Provisioning; Quality of service; Software-defined networking; Scalability; Computer network; Resource allocation; Distributed computing; Enhanced Data Rates for GSM Evolution; Controller (irrigation); Resource management (computing); Operating system; Telecommunications","routes":{"ca_aff":true,"ca_fund":true,"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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0004312477,0.0002799736,0.0003092371,0.0001011838,0.0002058718,0.0006018923,0.00252139,0.0002658662,0.00008824989],"category_scores_gemma":[0.0001353222,0.0002666545,0.0001312908,0.001178701,0.00004140716,0.000679837,0.0002403895,0.0003993467,0.0004517104],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000667979,"about_ca_system_score_gemma":0.0001380905,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004203758,"about_ca_topic_score_gemma":0.00001225333,"domain_scores_codex":[0.9976647,0.0001217764,0.0003620026,0.0007366529,0.0004555339,0.000659345],"domain_scores_gemma":[0.997044,0.0009504908,0.0002130558,0.001487774,0.0001374509,0.00016726],"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":[0.0001406586,0.0002608357,0.1723966,0.0001478912,0.00009061489,0.00003904057,0.0004135809,0.4455657,0.00004849464,0.04245894,0.2358681,0.1025695],"study_design_scores_gemma":[0.004369387,0.0007509742,0.08287997,0.001602849,0.0001141301,0.00003828199,0.0000252962,0.406941,0.003101539,0.1111651,0.3851023,0.003909265],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03721854,0.0004627754,0.9556522,0.001058592,0.003610904,0.0003798134,0.000002613049,0.0008569821,0.0007575284],"genre_scores_gemma":[0.9110662,0.00001378383,0.07898819,0.007700241,0.001711712,0.00006485153,0.00002553623,0.00005656373,0.0003729297],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.876664,"threshold_uncertainty_score":0.9999785,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02031399195261653,"score_gpt":0.2654766996466801,"score_spread":0.2451627076940636,"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."}}