{"id":"W2809114068","doi":"10.1007/978-3-319-94472-2_9","title":"Cloud Resource Allocation Based on Historical Records: An Analysis of Different Resource Estimation Functions","year":2018,"lang":"en","type":"book-chapter","venue":"Lecture notes in computer science","topic":"Cloud Computing and Resource Management","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"Carleton University","funders":"","keywords":"Computer science; CloudSim; Resource allocation; Cloud computing; Resource (disambiguation); Operations research; Distributed computing; Mathematical optimization; Data mining; Computer network","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":[0.00376392,0.0005261821,0.0006593004,0.001391934,0.000322202,0.001255119,0.001004342,0.0006792565,0.0009775544],"category_scores_gemma":[0.01314143,0.0002989267,0.0006944779,0.002578057,0.0003744929,0.002113694,0.0003317002,0.0006860148,0.0002261791],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008929775,"about_ca_system_score_gemma":0.0004081139,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005813122,"about_ca_topic_score_gemma":0.002868878,"domain_scores_codex":[0.9991724,0.0002266935,0.00005707855,0.0001704473,0.0002613415,0.0001121014],"domain_scores_gemma":[0.9873698,0.01001439,0.0006857829,0.0007128022,0.001090879,0.0001263263],"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":[0.001149297,0.0003112911,0.1330388,0.0003874424,0.0004222599,0.0004675998,0.0003258295,0.6120405,0.006534946,0.01249303,0.002636154,0.2301927],"study_design_scores_gemma":[0.000005236313,0.00005383294,0.03899558,0.00002464233,0.00008670511,0.0001197721,0.00007185304,0.9571215,0.001628588,0.001409013,0.0004643924,0.00001884579],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.83869,0.002746839,0.1537822,0.0003340763,0.00005759297,0.00006540325,0.000856935,0.0003763988,0.003090549],"genre_scores_gemma":[0.9865883,0.0006783034,0.011084,0.00002009673,0.00003139953,0.00002456491,0.0008367744,0.00005277251,0.0006837433],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005813122,"threshold_uncertainty_score":0.01990575,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01726631647655102,"score_gpt":0.2367703220522429,"score_spread":0.2195040055756918,"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."}}