{"id":"https://openalex.org/W7130600550","doi":"https://doi.org/10.1145/3797952","title":"DEL4CW: Deep Expansion Learning for Cloud Workloads Prediction","display_name":"DEL4CW: Deep Expansion Learning for Cloud Workloads Prediction","publication_year":2026,"publication_date":"2026-02-19","ids":{"openalex":"https://openalex.org/W7130600550","doi":"https://doi.org/10.1145/3797952"},"language":"en","primary_location":{"id":"doi:10.1145/3797952","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3797952","pdf_url":null,"source":{"id":"https://openalex.org/S41523882","display_name":"ACM Transactions on Knowledge Discovery from Data","issn_l":"1556-4681","issn":["1556-4681","1556-472X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Knowledge Discovery from Data","raw_type":"journal-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/A5126437647","display_name":"Xiaoyu Shi","orcid":null},"institutions":[{"id":"https://openalex.org/I4210123021","display_name":"Chongqing Institute of Green and Intelligent Technology","ror":"https://ror.org/031npqv35","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210123021"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaoyu Shi","raw_affiliation_strings":["Chongqing Key Laboratory of Edge Intelligent Computing, Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences, Chongqing, China"],"raw_orcid":"https://orcid.org/0000-0002-4267-7795","affiliations":[{"raw_affiliation_string":"Chongqing Key Laboratory of Edge Intelligent Computing, Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences, Chongqing, China","institution_ids":["https://openalex.org/I4210123021"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Qiuyue Lv","orcid":"https://orcid.org/0009-0007-7675-7025"},"institutions":[{"id":"https://openalex.org/I10535382","display_name":"Chongqing University of Posts and Telecommunications","ror":"https://ror.org/03dgaqz26","country_code":"CN","type":"education","lineage":["https://openalex.org/I10535382"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qiuyue Lv","raw_affiliation_strings":["Chongqing University of Posts and Telecommunications, Chongqing, China"],"raw_orcid":"https://orcid.org/0009-0007-7675-7025","affiliations":[{"raw_affiliation_string":"Chongqing University of Posts and Telecommunications, Chongqing, China","institution_ids":["https://openalex.org/I10535382"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037490723","display_name":"Bingchao Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I10535382","display_name":"Chongqing University of Posts and Telecommunications","ror":"https://ror.org/03dgaqz26","country_code":"CN","type":"education","lineage":["https://openalex.org/I10535382"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Bingchao Wang","raw_affiliation_strings":["Chongqing University of Posts and Telecommunications, Chongqing, China"],"raw_orcid":"https://orcid.org/0009-0005-1846-6655","affiliations":[{"raw_affiliation_string":"Chongqing University of Posts and Telecommunications, Chongqing, China","institution_ids":["https://openalex.org/I10535382"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5126441432","display_name":"Hong Xie","orcid":null},"institutions":[{"id":"https://openalex.org/I126520041","display_name":"University of Science and Technology of China","ror":"https://ror.org/04c4dkn09","country_code":"CN","type":"education","lineage":["https://openalex.org/I126520041","https://openalex.org/I19820366"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hong Xie","raw_affiliation_strings":["School of Computer Science and Technology, University of Science and Technology of China, Hefei, China"],"raw_orcid":"https://orcid.org/0000-0001-7935-7210","affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, University of Science and Technology of China, Hefei, China","institution_ids":["https://openalex.org/I126520041"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5126438747","display_name":"Mingsheng Shang","orcid":null},"institutions":[{"id":"https://openalex.org/I4210123021","display_name":"Chongqing Institute of Green and Intelligent Technology","ror":"https://ror.org/031npqv35","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210123021"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Mingsheng Shang","raw_affiliation_strings":["Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences, Chongqing, China"],"raw_orcid":"https://orcid.org/0000-0002-7024-2270","affiliations":[{"raw_affiliation_string":"Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences, Chongqing, China","institution_ids":["https://openalex.org/I4210123021"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.17872967,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"20","issue":"4","first_page":"1","last_page":"33"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10101","display_name":"Cloud Computing and Resource Management","score":0.8945000171661377,"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":0.8945000171661377,"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":0.05609999969601631,"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/T14347","display_name":"Big Data and Digital Economy","score":0.005499999970197678,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/cloud-computing","display_name":"Cloud computing","score":0.8787999749183655},{"id":"https://openalex.org/keywords/interpretability","display_name":"Interpretability","score":0.8155999779701233},{"id":"https://openalex.org/keywords/workload","display_name":"Workload","score":0.7551000118255615},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.6748999953269958},{"id":"https://openalex.org/keywords/residual","display_name":"Residual","score":0.5390999913215637},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.47049999237060547},{"id":"https://openalex.org/keywords/inefficiency","display_name":"Inefficiency","score":0.4641000032424927},{"id":"https://openalex.org/keywords/time-series","display_name":"Time series","score":0.40709999203681946}],"concepts":[{"id":"https://openalex.org/C79974875","wikidata":"https://www.wikidata.org/wiki/Q483639","display_name":"Cloud computing","level":2,"score":0.8787999749183655},{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.8155999779701233},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8046000003814697},{"id":"https://openalex.org/C2778476105","wikidata":"https://www.wikidata.org/wiki/Q628539","display_name":"Workload","level":2,"score":0.7551000118255615},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6748999953269958},{"id":"https://openalex.org/C155512373","wikidata":"https://www.wikidata.org/wiki/Q287450","display_name":"Residual","level":2,"score":0.5390999913215637},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5171999931335449},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.47049999237060547},{"id":"https://openalex.org/C2778869765","wikidata":"https://www.wikidata.org/wiki/Q6028363","display_name":"Inefficiency","level":2,"score":0.4641000032424927},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.45890000462532043},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.448199987411499},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4440999925136566},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.40709999203681946},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.3993000090122223},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.35030001401901245},{"id":"https://openalex.org/C24338571","wikidata":"https://www.wikidata.org/wiki/Q2566298","display_name":"Autoregressive integrated moving average","level":3,"score":0.3452000021934509},{"id":"https://openalex.org/C119898033","wikidata":"https://www.wikidata.org/wiki/Q3433888","display_name":"Ensemble forecasting","level":2,"score":0.3452000021934509},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.33390000462532043},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.2838999927043915},{"id":"https://openalex.org/C206345919","wikidata":"https://www.wikidata.org/wiki/Q20380951","display_name":"Resource (disambiguation)","level":2,"score":0.28130000829696655},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.2694999873638153},{"id":"https://openalex.org/C2780023022","wikidata":"https://www.wikidata.org/wiki/Q1338171","display_name":"Compensation (psychology)","level":2,"score":0.26249998807907104},{"id":"https://openalex.org/C148483581","wikidata":"https://www.wikidata.org/wiki/Q446488","display_name":"Feature selection","level":2,"score":0.2515000104904175},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.250900000333786}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3797952","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3797952","pdf_url":null,"source":{"id":"https://openalex.org/S41523882","display_name":"ACM Transactions on Knowledge Discovery from Data","issn_l":"1556-4681","issn":["1556-4681","1556-472X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Knowledge Discovery from Data","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Decent work and economic growth","score":0.553679883480072,"id":"https://metadata.un.org/sdg/8"}],"awards":[{"id":"https://openalex.org/G4308658107","display_name":null,"funder_award_id":"62372427","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":10,"referenced_works":["https://openalex.org/W1495747516","https://openalex.org/W1996129112","https://openalex.org/W2021535663","https://openalex.org/W2144499799","https://openalex.org/W2764100055","https://openalex.org/W2782968911","https://openalex.org/W2980994438","https://openalex.org/W2986615528","https://openalex.org/W4226248752","https://openalex.org/W4292263648"],"related_works":[],"abstract_inverted_index":{"Cloud":[0],"Workload":[1],"Prediction":[2],"(CWP)":[3],"is":[4],"a":[5,52,68,134],"critical":[6],"task":[7],"in":[8,78,98,257],"cloud":[9,35,81,103,240],"computing,":[10],"essential":[11],"for":[12,63,149,210],"resource":[13],"scheduling,":[14],"performance":[15],"optimization,":[16],"and":[17,29,42,111,128,152],"cost":[18],"management.":[19],"However,":[20],"existing":[21,248],"time":[22],"series":[23],"prediction":[24,230],"methods":[25],"struggle":[26],"with":[27,250],"instability":[28],"inefficiency":[30],"when":[31],"applied":[32],"directly":[33],"to":[34,38,72,84,101,122,163,177,193,197,255],"workloads":[36],"due":[37],"their":[39],"high":[40],"variability":[41],"frequent":[43],"fluctuations.":[44],"To":[45],"address":[46],"these":[47,114],"challenges,":[48],"we":[49],"propose":[50],"DEL4CW,":[51],"novel":[53],"D":[54],"eep":[55],"E":[56],"xpansion":[57],"L":[58],"earning":[59],"framework":[60,138],"specifically":[61],"designed":[62],"CWP":[64],".":[65],"DEL4CW":[66,96,132,201,245],"introduces":[67],"unique":[69],"self-decoupling":[70],"mechanism":[71],"disentangle":[73],"the":[74,120,155,171,190,221],"complex":[75],"dependencies":[76],"present":[77],"highly":[79],"variable":[80],"workloads,":[82],"leading":[83],"more":[85],"accurate":[86],"predictions":[87],"of":[88,95,213],"job":[89],"arrival":[90],"rates.":[91],"The":[92,182],"core":[93],"contribution":[94],"lies":[97],"its":[99,198,206],"ability":[100],"decouple":[102],"workload":[104,130,241],"signals":[105],"into":[106],"three":[107],"key":[108],"components\u2014trend,":[109],"periodicity,":[110,151],"residuals\u2014by":[112],"treating":[113],"as":[115,140],"hidden":[116],"variables.":[117],"This":[118,217],"enables":[119],"model":[121],"better":[123],"manage":[124],"both":[125],"short-term":[126],"fluctuations":[127],"long-term":[129],"trends.":[131],"employs":[133],"deep":[135],"expansion":[136],"learning":[137,224],"structured":[139],"stacked":[141],"blocks,":[142],"where":[143],"each":[144,229],"block":[145,231],"includes":[146],"dedicated":[147],"modules":[148],"trend,":[150],"compensation.":[153],"Specifically,":[154],"trend":[156],"module":[157,173,184],"utilizes":[158],"multi-layer":[159],"fully":[160],"connected":[161],"networks":[162],"capture":[164],"evolving":[165],"trends":[166],"at":[167],"multiple":[168],"granularities,":[169],"while":[170],"periodicity":[172],"leverages":[174],"multi-head":[175],"attention":[176],"identify":[178],"diverse":[179],"periodic":[180],"patterns.":[181],"compensation":[183],"addresses":[185],"unpredictable,":[186],"localized":[187],"fluctuations,":[188],"improving":[189],"model\u2019s":[191],"robustness":[192],"noise.":[194],"In":[195],"addition":[196],"predictive":[199],"accuracy,":[200],"provides":[202],"interpretable":[203],"insights":[204],"through":[205],"hierarchical":[207],"design,":[208],"allowing":[209],"layer-by-layer":[211],"aggregation":[212],"meaningful":[214],"partial":[215],"predictions.":[216,235],"interpretability":[218],"stems":[219],"from":[220],"doubly":[222],"residual":[223],"pipeline,":[225],"which":[226],"ensures":[227],"that":[228,244],"contributes":[232],"progressively":[233],"refined":[234],"Extensive":[236],"experiments":[237],"on":[238],"real-world":[239],"traces":[242],"demonstrate":[243],"significantly":[246],"outperforms":[247],"baselines,":[249],"error":[251],"reductions":[252],"reaching":[253],"up":[254],"27.74%":[256],"certain":[258],"scenarios.":[259]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-02-20T00:00:00"}
