{"id":"https://openalex.org/W2964694872","doi":"https://doi.org/10.1109/icess.2019.8782503","title":"Efficient Cloud Resource Management using Neuromorphic Modeling and Prediction for Virtual Machine Resource Utilization","display_name":"Efficient Cloud Resource Management using Neuromorphic Modeling and Prediction for Virtual Machine Resource Utilization","publication_year":2019,"publication_date":"2019-06-01","ids":{"openalex":"https://openalex.org/W2964694872","doi":"https://doi.org/10.1109/icess.2019.8782503","mag":"2964694872"},"language":"en","primary_location":{"id":"doi:10.1109/icess.2019.8782503","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icess.2019.8782503","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE International Conference on Embedded Software and Systems (ICESS)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100356606","display_name":"Zhe Li","orcid":"https://orcid.org/0000-0001-7056-4133"},"institutions":[{"id":"https://openalex.org/I70983195","display_name":"Syracuse University","ror":"https://ror.org/025r5qe02","country_code":"US","type":"education","lineage":["https://openalex.org/I70983195"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zhe Li","raw_affiliation_strings":["Department of Electrical Engineering and Computer Science, Syracuse University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering and Computer Science, Syracuse University","institution_ids":["https://openalex.org/I70983195"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5016070401","display_name":"Xiaolong Ma","orcid":"https://orcid.org/0000-0003-3753-7648"},"institutions":[{"id":"https://openalex.org/I12912129","display_name":"Northeastern University","ror":"https://ror.org/04t5xt781","country_code":"US","type":"education","lineage":["https://openalex.org/I12912129"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Xiaolong Ma","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Northeastern University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Northeastern University","institution_ids":["https://openalex.org/I12912129"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100421180","display_name":"Ji Li","orcid":"https://orcid.org/0000-0003-4699-084X"},"institutions":[{"id":"https://openalex.org/I1174212","display_name":"University of Southern California","ror":"https://ror.org/03taz7m60","country_code":"US","type":"education","lineage":["https://openalex.org/I1174212"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ji Li","raw_affiliation_strings":["Department of Electrical and Computer Engineering, University of Southern California"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, University of Southern California","institution_ids":["https://openalex.org/I1174212"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5018468480","display_name":"Qinru Qiu","orcid":"https://orcid.org/0000-0003-2546-0655"},"institutions":[{"id":"https://openalex.org/I70983195","display_name":"Syracuse University","ror":"https://ror.org/025r5qe02","country_code":"US","type":"education","lineage":["https://openalex.org/I70983195"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Qinru Qiu","raw_affiliation_strings":["Department of Electrical Engineering and Computer Science, Syracuse University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering and Computer Science, Syracuse University","institution_ids":["https://openalex.org/I70983195"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100651384","display_name":"Yanzhi Wang","orcid":"https://orcid.org/0000-0002-3024-7990"},"institutions":[{"id":"https://openalex.org/I12912129","display_name":"Northeastern University","ror":"https://ror.org/04t5xt781","country_code":"US","type":"education","lineage":["https://openalex.org/I12912129"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yanzhi Wang","raw_affiliation_strings":["Department of Electrical and Computer Engineering, Northeastern University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, Northeastern University","institution_ids":["https://openalex.org/I12912129"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.439,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.59418969,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"428","issue":null,"first_page":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10101","display_name":"Cloud Computing and Resource Management","score":0.9986000061035156,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10101","display_name":"Cloud Computing and Resource Management","score":0.9986000061035156,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12676","display_name":"Machine Learning and ELM","score":0.9919999837875366,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10320","display_name":"Neural Networks and Applications","score":0.9842000007629395,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8055564165115356},{"id":"https://openalex.org/keywords/cloud-computing","display_name":"Cloud computing","score":0.6723688840866089},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5411670804023743},{"id":"https://openalex.org/keywords/resource","display_name":"Resource (disambiguation)","score":0.5250900983810425},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5171051025390625},{"id":"https://openalex.org/keywords/neuromorphic-engineering","display_name":"Neuromorphic engineering","score":0.5115000009536743},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.4865330755710602},{"id":"https://openalex.org/keywords/resource-management","display_name":"Resource management (computing)","score":0.44602033495903015},{"id":"https://openalex.org/keywords/resource-allocation","display_name":"Resource allocation","score":0.4212174415588379},{"id":"https://openalex.org/keywords/virtual-machine","display_name":"Virtual machine","score":0.4146648049354553},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.3983934223651886},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3635196089744568},{"id":"https://openalex.org/keywords/distributed-computing","display_name":"Distributed computing","score":0.2986164093017578}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8055564165115356},{"id":"https://openalex.org/C79974875","wikidata":"https://www.wikidata.org/wiki/Q483639","display_name":"Cloud computing","level":2,"score":0.6723688840866089},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5411670804023743},{"id":"https://openalex.org/C206345919","wikidata":"https://www.wikidata.org/wiki/Q20380951","display_name":"Resource (disambiguation)","level":2,"score":0.5250900983810425},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5171051025390625},{"id":"https://openalex.org/C151927369","wikidata":"https://www.wikidata.org/wiki/Q1981312","display_name":"Neuromorphic engineering","level":3,"score":0.5115000009536743},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.4865330755710602},{"id":"https://openalex.org/C2780609101","wikidata":"https://www.wikidata.org/wiki/Q17156588","display_name":"Resource management (computing)","level":2,"score":0.44602033495903015},{"id":"https://openalex.org/C29202148","wikidata":"https://www.wikidata.org/wiki/Q287260","display_name":"Resource allocation","level":2,"score":0.4212174415588379},{"id":"https://openalex.org/C25344961","wikidata":"https://www.wikidata.org/wiki/Q192726","display_name":"Virtual machine","level":2,"score":0.4146648049354553},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3983934223651886},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3635196089744568},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.2986164093017578},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icess.2019.8782503","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icess.2019.8782503","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE International Conference on Embedded Software and Systems (ICESS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Affordable and clean energy","score":0.5600000023841858,"id":"https://metadata.un.org/sdg/7"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W1678889691","https://openalex.org/W1975714674","https://openalex.org/W2016210396","https://openalex.org/W2025852542","https://openalex.org/W2031239257","https://openalex.org/W2033892038","https://openalex.org/W2044794176","https://openalex.org/W2049287603","https://openalex.org/W2068867834","https://openalex.org/W2078012618","https://openalex.org/W2125663122","https://openalex.org/W2129532872","https://openalex.org/W2137695118","https://openalex.org/W2140190241","https://openalex.org/W2147078261","https://openalex.org/W2147738849","https://openalex.org/W2149921893","https://openalex.org/W2152376172","https://openalex.org/W2170079875","https://openalex.org/W2610383189","https://openalex.org/W3015297855","https://openalex.org/W3021389266","https://openalex.org/W4211064163","https://openalex.org/W4247709344","https://openalex.org/W4252624212","https://openalex.org/W6736956795"],"related_works":["https://openalex.org/W2923452570","https://openalex.org/W206598027","https://openalex.org/W2978610750","https://openalex.org/W2022931285","https://openalex.org/W1589966275","https://openalex.org/W2904351595","https://openalex.org/W2086872282","https://openalex.org/W2137789903","https://openalex.org/W2153007255","https://openalex.org/W2138781885"],"abstract_inverted_index":{"With":[0],"the":[1,49,86,100,118,125,156,162,168],"rapid":[2],"development":[3],"of":[4,91,173],"Cloud":[5],"Computing":[6],"and":[7,61,107,142],"Data":[8],"Centers,":[9],"Virtual":[10,32,130],"Machine":[11,33,131],"consolidation":[12],"has":[13,143],"become":[14],"an":[15,53,144],"important":[16],"issue":[17],"to":[18,24,51,84,112,116,178],"achieve":[19],"economic":[20],"scale.":[21],"In":[22,72],"order":[23],"support":[25,117],"such":[26,42],"feature,":[27],"a":[28,57,75,109,136,151],"robust":[29],"scheme":[30],"for":[31,56],"resource":[34,87,132,160,164],"demands":[35],"prediction":[36,40,59,119,134,149,153],"is":[37,82],"critical.":[38],"Previous":[39],"models":[41,108],"as":[43],"Auto-Regressive":[44],"Moving":[45],"Average":[46],"model":[47,128],"lacks":[48],"ability":[50],"give":[52],"acceptable":[54],"accuracy":[55,138],"large":[58],"window":[60],"conventional":[62],"machine":[63],"learning":[64],"based":[65,78,129],"methods":[66],"suffer":[67],"from":[68,89],"high":[69],"complexity":[70],"problem.":[71],"this":[73],"work,":[74],"neuromorphic":[76],"system":[77,98],"on":[79],"cogent":[80,126],"confabulation":[81,127],"built":[83],"predict":[85],"usages":[88],"statistics":[90],"historical":[92],"records":[93],"in":[94,104,147],"comprehensive":[95],"dimensions.":[96],"The":[97,121],"exploits":[99],"correlations":[101],"between":[102],"observations":[103],"multiple":[105],"dimensions":[106],"probability":[110],"network":[111],"be":[113],"finely":[114],"tuned":[115],"application.":[120],"experimental":[122],"results":[123],"show":[124],"utilization":[133],"gives":[135],"better":[137],"than":[139],"previous":[140],"work":[141],"intrinsic":[145],"advantage":[146],"dynamic":[148],"with":[150],"wider":[152],"window.":[154],"Using":[155],"accurate":[157],"confabulation-based":[158],"VM":[159],"prediction,":[161],"cloud":[163],"management":[165],"can":[166],"improve":[167],"energy":[169],"efficiency":[170],"(in":[171],"terms":[172],"electricity":[174],"price)":[175],"by":[176],"up":[177],"26.52%.":[179]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
