{"id":"https://openalex.org/W2894915928","doi":"https://doi.org/10.1109/dsmp.2018.8478443","title":"Cloud Datacenter Workload Prediction Using Complex-Valued Neural Networks","display_name":"Cloud Datacenter Workload Prediction Using Complex-Valued Neural Networks","publication_year":2018,"publication_date":"2018-08-01","ids":{"openalex":"https://openalex.org/W2894915928","doi":"https://doi.org/10.1109/dsmp.2018.8478443","mag":"2894915928"},"language":"en","primary_location":{"id":"doi:10.1109/dsmp.2018.8478443","is_oa":false,"landing_page_url":"https://doi.org/10.1109/dsmp.2018.8478443","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE Second International Conference on Data Stream Mining &amp; Processing (DSMP)","raw_type":"proceedings-article"},"type":"article","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/A5045316797","display_name":"Kashifuddin Qazi","orcid":"https://orcid.org/0000-0002-3423-2657"},"institutions":[{"id":"https://openalex.org/I55707380","display_name":"Manhattan University","ror":"https://ror.org/02xhnzg94","country_code":"US","type":"education","lineage":["https://openalex.org/I55707380"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kashifuddin Qazi","raw_affiliation_strings":["Department of Computer Science, Manhattan College, New York, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Manhattan College, New York, USA","institution_ids":["https://openalex.org/I55707380"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5052101553","display_name":"Igor Aizenberg","orcid":"https://orcid.org/0000-0002-5994-6568"},"institutions":[{"id":"https://openalex.org/I55707380","display_name":"Manhattan University","ror":"https://ror.org/02xhnzg94","country_code":"US","type":"education","lineage":["https://openalex.org/I55707380"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Igor Aizenberg","raw_affiliation_strings":["Department of Computer Science, Manhattan College, New York, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, Manhattan College, New York, USA","institution_ids":["https://openalex.org/I55707380"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.0566,"has_fulltext":false,"cited_by_count":11,"citation_normalized_percentile":{"value":0.90621882,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"315","last_page":"321"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10101","display_name":"Cloud Computing and Resource Management","score":0.9997000098228455,"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":0.9997000098228455,"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/T12127","display_name":"Software System Performance and Reliability","score":0.9894999861717224,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T10273","display_name":"IoT and Edge/Fog Computing","score":0.9810000061988831,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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":0.8355032205581665},{"id":"https://openalex.org/keywords/cloud-computing","display_name":"Cloud computing","score":0.7854917049407959},{"id":"https://openalex.org/keywords/distributed-computing","display_name":"Distributed computing","score":0.713654637336731},{"id":"https://openalex.org/keywords/workload","display_name":"Workload","score":0.6879683136940002},{"id":"https://openalex.org/keywords/load-balancing","display_name":"Load balancing (electrical power)","score":0.5962187051773071},{"id":"https://openalex.org/keywords/host","display_name":"Host (biology)","score":0.5455966591835022},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5181390047073364},{"id":"https://openalex.org/keywords/energy-consumption","display_name":"Energy consumption","score":0.44943535327911377},{"id":"https://openalex.org/keywords/resource-management","display_name":"Resource management (computing)","score":0.4352649450302124},{"id":"https://openalex.org/keywords/grid","display_name":"Grid","score":0.4034690856933594},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.3488706350326538},{"id":"https://openalex.org/keywords/operating-system","display_name":"Operating system","score":0.24252033233642578},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.17217400670051575},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.08923760056495667}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8355032205581665},{"id":"https://openalex.org/C79974875","wikidata":"https://www.wikidata.org/wiki/Q483639","display_name":"Cloud computing","level":2,"score":0.7854917049407959},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.713654637336731},{"id":"https://openalex.org/C2778476105","wikidata":"https://www.wikidata.org/wiki/Q628539","display_name":"Workload","level":2,"score":0.6879683136940002},{"id":"https://openalex.org/C138959212","wikidata":"https://www.wikidata.org/wiki/Q1806783","display_name":"Load balancing (electrical power)","level":3,"score":0.5962187051773071},{"id":"https://openalex.org/C126831891","wikidata":"https://www.wikidata.org/wiki/Q221673","display_name":"Host (biology)","level":2,"score":0.5455966591835022},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5181390047073364},{"id":"https://openalex.org/C2780165032","wikidata":"https://www.wikidata.org/wiki/Q16869822","display_name":"Energy consumption","level":2,"score":0.44943535327911377},{"id":"https://openalex.org/C2780609101","wikidata":"https://www.wikidata.org/wiki/Q17156588","display_name":"Resource management (computing)","level":2,"score":0.4352649450302124},{"id":"https://openalex.org/C187691185","wikidata":"https://www.wikidata.org/wiki/Q2020720","display_name":"Grid","level":2,"score":0.4034690856933594},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.3488706350326538},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.24252033233642578},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.17217400670051575},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.08923760056495667},{"id":"https://openalex.org/C18903297","wikidata":"https://www.wikidata.org/wiki/Q7150","display_name":"Ecology","level":1,"score":0.0},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/dsmp.2018.8478443","is_oa":false,"landing_page_url":"https://doi.org/10.1109/dsmp.2018.8478443","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE Second International Conference on Data Stream Mining &amp; Processing (DSMP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/7","display_name":"Affordable and clean energy","score":0.47999998927116394}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":23,"referenced_works":["https://openalex.org/W1594058661","https://openalex.org/W2005568463","https://openalex.org/W2017107867","https://openalex.org/W2019472314","https://openalex.org/W2027262587","https://openalex.org/W2030259025","https://openalex.org/W2047515252","https://openalex.org/W2048361500","https://openalex.org/W2075168211","https://openalex.org/W2106098710","https://openalex.org/W2108827210","https://openalex.org/W2122494490","https://openalex.org/W2136510202","https://openalex.org/W2136892987","https://openalex.org/W2144802575","https://openalex.org/W2161694749","https://openalex.org/W2178055113","https://openalex.org/W2580794816","https://openalex.org/W2608354815","https://openalex.org/W2890457559","https://openalex.org/W4253305097","https://openalex.org/W6669435852","https://openalex.org/W6736911978"],"related_works":["https://openalex.org/W986318368","https://openalex.org/W2000785801","https://openalex.org/W2384410913","https://openalex.org/W2352878646","https://openalex.org/W2004734601","https://openalex.org/W2130149817","https://openalex.org/W2990194547","https://openalex.org/W1480123525","https://openalex.org/W2620865396","https://openalex.org/W2414054180"],"abstract_inverted_index":{"Cloud":[0],"computing":[1],"infrastructures":[2],"and":[3,14,27,44,47],"datacenters":[4],"depend":[5],"on":[6,90,118],"intelligent":[7],"management":[8],"of":[9,19,41,56,69],"underlying":[10],"CPU,":[11],"memory,":[12],"network,":[13],"storage":[15],"resources.":[16,79],"A":[17],"variety":[18],"techniques":[20],"such":[21],"as":[22,127,129,150,152],"load":[23,25,121,133],"balancing,":[24],"consolidation,":[26],"remote":[28],"memory":[29],"allocation":[30],"are":[31],"used":[32],"to":[33,104,106,146],"maintain":[34],"a":[35,83,91],"fine":[36],"balance":[37],"between":[38],"conflicting":[39],"goals":[40],"high":[42],"performance,":[43],"low":[45],"costs":[46],"energy":[48],"consumption.":[49],"To":[50],"meet":[51],"these":[52],"goals,":[53],"successful":[54],"prediction":[55,87,144],"the":[57,66,77],"workloads":[58],"is":[59,101,116,137],"an":[60],"important":[61],"problem.":[62],"By":[63],"accurately":[64],"predicting":[65],"resource":[67,85],"utilization":[68],"host":[70,84],"machines,":[71],"datacenter":[72,112],"owners":[73],"can":[74],"better":[75],"manage":[76],"available":[78],"This":[80],"paper":[81],"presents":[82],"usage":[86],"approach,":[88],"based":[89,132],"Multilayer":[92],"Neural":[93],"Network":[94],"with":[95],"Multi-Valued":[96],"Neurons":[97],"(MLMVN).":[98],"An":[99],"enhancement":[100],"further":[102],"implemented":[103],"MLMVN":[105],"make":[107],"it":[108],"suitable":[109],"for":[110],"cloud":[111],"applications.":[113],"The":[114,135],"approach":[115],"evaluated":[117],"real":[119],"world":[120],"traces":[122],"from":[123],"Google's":[124],"cluster":[125],"data,":[126],"well":[128,151],"two":[130],"grid":[131],"traces.":[134],"algorithm":[136],"compared":[138],"against":[139],"some":[140],"current":[141],"state-of-the-art":[142],"host-load":[143],"algorithms":[145],"show":[147],"its":[148],"accuracy,":[149],"performance":[153],"gains.":[154]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
