{"id":"W2025912826","doi":"10.1109/glocom.2014.7037508","title":"Resource sharing for software defined D2D communications in virtual wireless networks with imperfect NSI","year":2014,"lang":"en","type":"article","venue":"","topic":"Advanced MIMO Systems Optimization","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Wireless network; Distributed computing; Wireless; Virtualization; Software-defined networking; Resource allocation; Software; Computer network; Stochastic geometry; Stochastic geometry models of wireless networks; Virtual network; Shared resource; Radio resource management; Controller (irrigation); Optimization problem; Algorithm; Telecommunications; Cloud computing","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":[],"consensus_categories":[],"category_scores_codex":[0.0001853773,0.0001338692,0.0001790026,0.0000759066,0.00007737379,0.00002968409,0.0002747905,0.00007965312,0.000003935786],"category_scores_gemma":[0.00003404924,0.0001264013,0.00002452437,0.0002078765,0.00002426691,0.0001419535,0.00006567163,0.0001362296,0.000003187932],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007870494,"about_ca_system_score_gemma":0.000005774007,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002174197,"about_ca_topic_score_gemma":0.0005414615,"domain_scores_codex":[0.9993148,0.00002257073,0.0002183218,0.0001663518,0.00005042997,0.0002275286],"domain_scores_gemma":[0.9989769,0.0002940856,0.00003377656,0.0006130025,0.00003878487,0.00004346357],"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":[0.00001208521,0.000007597862,0.001696638,0.00002421721,0.000009868656,1.248251e-7,0.0001110193,0.9868345,0.00007634631,0.002084156,0.0001211955,0.009022214],"study_design_scores_gemma":[0.0005916083,0.00004840033,0.0001062864,0.00008790141,0.00000703815,0.000002852727,0.00009009605,0.99757,0.0001311066,0.00004131001,0.001147178,0.0001761901],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.007989129,0.00008519553,0.9893236,0.00002666149,0.00004118764,0.0003688146,0.000002318821,0.0004719161,0.001691156],"genre_scores_gemma":[0.9343641,0.00001558937,0.06508106,0.00003459249,0.00004419602,0.000161176,0.00006392471,0.00006584315,0.0001694681],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.926375,"threshold_uncertainty_score":0.5154497,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01080286646833649,"score_gpt":0.2221081461209335,"score_spread":0.211305279652597,"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."}}