{"id":"W2955847099","doi":"10.1109/ccgrid.2019.00045","title":"CRAM: a Container Resource Allocation Mechanism for Big Data Streaming Applications","year":2019,"lang":"en","type":"article","venue":"","topic":"Cloud Computing and Resource Management","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Computer science; Quality of service; Resource allocation; Nash equilibrium; Container (type theory); Cloud computing; Game theory; Distributed computing; Resource management (computing); Workload; Resource (disambiguation); Key (lock); Computer network; Mathematical optimization; Computer security; Operating system","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":[0.001926116,0.0008044534,0.000689215,0.0009824496,0.0009299908,0.001230438,0.003250819,0.0009654611,0.002414339],"category_scores_gemma":[0.002649889,0.0004136362,0.0007198691,0.0007263505,0.0007971996,0.001991941,0.002192385,0.001374738,0.0005637205],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001006644,"about_ca_system_score_gemma":0.001676222,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002615931,"about_ca_topic_score_gemma":0.002787608,"domain_scores_codex":[0.9989908,0.0002842328,0.00006874604,0.0002036542,0.000279911,0.000172662],"domain_scores_gemma":[0.9985917,0.0002866769,0.0002778101,0.0003543199,0.0002448976,0.0002445741],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001890346,0.001305898,0.004136401,0.0008419955,0.0004682115,0.001146453,0.0006305181,0.2340769,0.160272,0.113742,0.04748585,0.4340035],"study_design_scores_gemma":[0.0001141841,0.0002703218,0.0007003862,0.00002416834,0.0000439928,0.0002745667,0.00006040676,0.9626195,0.01564356,0.006612863,0.0135527,0.0000834092],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.03883714,0.0005373012,0.9451942,0.0004014363,0.000227218,0.0006506692,0.0001291488,0.008865341,0.005157561],"genre_scores_gemma":[0.6220403,0.0003165706,0.3710949,0.0003112744,0.0001394933,0.0006143299,0.0002267243,0.0004173033,0.004839079],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003250819,"threshold_uncertainty_score":0.01018637,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03826527020160782,"score_gpt":0.259305506349879,"score_spread":0.2210402361482712,"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."}}