{"id":"https://openalex.org/W7160345560","doi":"https://doi.org/10.1155/acis/1160180","title":"An LSTM\u2010Based Resource Prediction Model in Google Cloud Data Center","display_name":"An LSTM\u2010Based Resource Prediction Model in Google Cloud Data Center","publication_year":2026,"publication_date":"2026-01-01","ids":{"openalex":"https://openalex.org/W7160345560","doi":"https://doi.org/10.1155/acis/1160180"},"language":"en","primary_location":{"id":"doi:10.1155/acis/1160180","is_oa":true,"landing_page_url":"https://doi.org/10.1155/acis/1160180","pdf_url":null,"source":{"id":"https://openalex.org/S30680879","display_name":"Applied Computational Intelligence and Soft Computing","issn_l":"1687-9724","issn":["1687-9724","1687-9732"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319869","host_organization_name":"Hindawi Publishing Corporation","host_organization_lineage":["https://openalex.org/P4310319869"],"host_organization_lineage_names":["Hindawi Publishing Corporation"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Applied Computational Intelligence and Soft Computing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1155/acis/1160180","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5135289454","display_name":"Eman Alshboul","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Eman Alshboul","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5055512040","display_name":"Husam Suleiman","orcid":"https://orcid.org/0000-0003-3805-7603"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Husam Suleiman","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0000-0003-3805-7603","affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5135305211","display_name":"Mohammad Alshboul","orcid":"https://orcid.org/0009-0008-3603-1729"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Mohammad Alshboul","raw_affiliation_strings":[],"raw_orcid":"https://orcid.org/0009-0008-3603-1729","affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":900,"currency":"USD","value_usd":900},"apc_paid":{"value":900,"currency":"USD","value_usd":900},"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.73497294,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"2026","issue":"1","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10101","display_name":"Cloud Computing and Resource Management","score":0.8585000038146973,"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":0.8585000038146973,"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":0.03009999915957451,"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":0.018200000748038292,"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/workload","display_name":"Workload","score":0.795799970626831},{"id":"https://openalex.org/keywords/cloud-computing","display_name":"Cloud computing","score":0.7335000038146973},{"id":"https://openalex.org/keywords/autoregressive-integrated-moving-average","display_name":"Autoregressive integrated moving average","score":0.5275999903678894},{"id":"https://openalex.org/keywords/autoregressive-model","display_name":"Autoregressive model","score":0.4717999994754791},{"id":"https://openalex.org/keywords/decision-tree","display_name":"Decision tree","score":0.45809999108314514},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.45570001006126404},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.43529999256134033},{"id":"https://openalex.org/keywords/trace","display_name":"TRACE (psycholinguistics)","score":0.4250999987125397},{"id":"https://openalex.org/keywords/data-center","display_name":"Data center","score":0.41530001163482666},{"id":"https://openalex.org/keywords/gradient-boosting","display_name":"Gradient boosting","score":0.4081999957561493}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.9027000069618225},{"id":"https://openalex.org/C2778476105","wikidata":"https://www.wikidata.org/wiki/Q628539","display_name":"Workload","level":2,"score":0.795799970626831},{"id":"https://openalex.org/C79974875","wikidata":"https://www.wikidata.org/wiki/Q483639","display_name":"Cloud computing","level":2,"score":0.7335000038146973},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.551800012588501},{"id":"https://openalex.org/C24338571","wikidata":"https://www.wikidata.org/wiki/Q2566298","display_name":"Autoregressive integrated moving average","level":3,"score":0.5275999903678894},{"id":"https://openalex.org/C159877910","wikidata":"https://www.wikidata.org/wiki/Q2202883","display_name":"Autoregressive model","level":2,"score":0.4717999994754791},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.47130000591278076},{"id":"https://openalex.org/C84525736","wikidata":"https://www.wikidata.org/wiki/Q831366","display_name":"Decision tree","level":2,"score":0.45809999108314514},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.45570001006126404},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.43529999256134033},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4350999891757965},{"id":"https://openalex.org/C75291252","wikidata":"https://www.wikidata.org/wiki/Q1315756","display_name":"TRACE (psycholinguistics)","level":2,"score":0.4250999987125397},{"id":"https://openalex.org/C153740404","wikidata":"https://www.wikidata.org/wiki/Q671224","display_name":"Data center","level":2,"score":0.41530001163482666},{"id":"https://openalex.org/C70153297","wikidata":"https://www.wikidata.org/wiki/Q5591907","display_name":"Gradient boosting","level":3,"score":0.4081999957561493},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.39320001006126404},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.3917999863624573},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.37709999084472656},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.37040001153945923},{"id":"https://openalex.org/C45804977","wikidata":"https://www.wikidata.org/wiki/Q7239673","display_name":"Predictive modelling","level":2,"score":0.36890000104904175},{"id":"https://openalex.org/C206345919","wikidata":"https://www.wikidata.org/wiki/Q20380951","display_name":"Resource (disambiguation)","level":2,"score":0.3384999930858612},{"id":"https://openalex.org/C164866538","wikidata":"https://www.wikidata.org/wiki/Q367351","display_name":"Cluster (spacecraft)","level":2,"score":0.3255000114440918},{"id":"https://openalex.org/C2780378061","wikidata":"https://www.wikidata.org/wiki/Q25351891","display_name":"Service (business)","level":2,"score":0.31949999928474426},{"id":"https://openalex.org/C113174947","wikidata":"https://www.wikidata.org/wiki/Q2859736","display_name":"Tree (set theory)","level":2,"score":0.2955000102519989},{"id":"https://openalex.org/C29202148","wikidata":"https://www.wikidata.org/wiki/Q287260","display_name":"Resource allocation","level":2,"score":0.2937000095844269},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.28929999470710754},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.2874999940395355},{"id":"https://openalex.org/C5119721","wikidata":"https://www.wikidata.org/wiki/Q220501","display_name":"Quality of service","level":2,"score":0.27880001068115234},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.27410000562667847},{"id":"https://openalex.org/C151406439","wikidata":"https://www.wikidata.org/wiki/Q186588","display_name":"Time series","level":2,"score":0.27379998564720154},{"id":"https://openalex.org/C19012869","wikidata":"https://www.wikidata.org/wiki/Q578372","display_name":"Response time","level":2,"score":0.2648000121116638},{"id":"https://openalex.org/C29140674","wikidata":"https://www.wikidata.org/wiki/Q206637","display_name":"Computer cluster","level":2,"score":0.2614000141620636},{"id":"https://openalex.org/C116537","wikidata":"https://www.wikidata.org/wiki/Q2169973","display_name":"Service provider","level":3,"score":0.2535000145435333},{"id":"https://openalex.org/C127964446","wikidata":"https://www.wikidata.org/wiki/Q1092142","display_name":"Computational resource","level":3,"score":0.2506999969482422}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1155/acis/1160180","is_oa":true,"landing_page_url":"https://doi.org/10.1155/acis/1160180","pdf_url":null,"source":{"id":"https://openalex.org/S30680879","display_name":"Applied Computational Intelligence and Soft Computing","issn_l":"1687-9724","issn":["1687-9724","1687-9732"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319869","host_organization_name":"Hindawi Publishing Corporation","host_organization_lineage":["https://openalex.org/P4310319869"],"host_organization_lineage_names":["Hindawi Publishing Corporation"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Applied Computational Intelligence and Soft Computing","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1155/acis/1160180","is_oa":true,"landing_page_url":"https://doi.org/10.1155/acis/1160180","pdf_url":null,"source":{"id":"https://openalex.org/S30680879","display_name":"Applied Computational Intelligence and Soft Computing","issn_l":"1687-9724","issn":["1687-9724","1687-9732"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319869","host_organization_name":"Hindawi Publishing Corporation","host_organization_lineage":["https://openalex.org/P4310319869"],"host_organization_lineage_names":["Hindawi Publishing Corporation"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Applied Computational Intelligence and Soft Computing","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.4720233380794525,"display_name":"Decent work and economic growth","id":"https://metadata.un.org/sdg/8"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":62,"referenced_works":["https://openalex.org/W1984255960","https://openalex.org/W2000659534","https://openalex.org/W2018836191","https://openalex.org/W2019472314","https://openalex.org/W2062458580","https://openalex.org/W2064675550","https://openalex.org/W2092592878","https://openalex.org/W2115743854","https://openalex.org/W2129542763","https://openalex.org/W2143039774","https://openalex.org/W2169125069","https://openalex.org/W2282727795","https://openalex.org/W2477897077","https://openalex.org/W2491816934","https://openalex.org/W2506822277","https://openalex.org/W2508635334","https://openalex.org/W2575635164","https://openalex.org/W2608354815","https://openalex.org/W2727810769","https://openalex.org/W2754252319","https://openalex.org/W2757854249","https://openalex.org/W2782968911","https://openalex.org/W2809539044","https://openalex.org/W2892341857","https://openalex.org/W2901895730","https://openalex.org/W2923185253","https://openalex.org/W2935905456","https://openalex.org/W2943296966","https://openalex.org/W2944851425","https://openalex.org/W2964211630","https://openalex.org/W2968629186","https://openalex.org/W2969851632","https://openalex.org/W2986615528","https://openalex.org/W2992296379","https://openalex.org/W3005641657","https://openalex.org/W3007083472","https://openalex.org/W3032515432","https://openalex.org/W3035965352","https://openalex.org/W3089344842","https://openalex.org/W3114767465","https://openalex.org/W3120636638","https://openalex.org/W3121678941","https://openalex.org/W3122391591","https://openalex.org/W3136021864","https://openalex.org/W3138270325","https://openalex.org/W3140854437","https://openalex.org/W3153977456","https://openalex.org/W3159651000","https://openalex.org/W3164246203","https://openalex.org/W3200069532","https://openalex.org/W4281674262","https://openalex.org/W4285078834","https://openalex.org/W4293024032","https://openalex.org/W4308621130","https://openalex.org/W4318483001","https://openalex.org/W4379799065","https://openalex.org/W4381465310","https://openalex.org/W4390740124","https://openalex.org/W4392902287","https://openalex.org/W4398174014","https://openalex.org/W4413631928","https://openalex.org/W7084056374"],"related_works":[],"abstract_inverted_index":{"The":[0,46,128,169],"increasing":[1],"complexity":[2],"and":[3,104,165,182,209,233],"dynamic":[4],"nature":[5],"of":[6,33,42,53,86,89,106,123,195,204,212],"workloads":[7,55],"in":[8,134,198],"cloud":[9,97],"computing":[10],"are":[11],"characterized":[12],"by":[13,30],"various":[14,73,152],"patterns":[15],"with":[16,37,146,200],"time\u2010dependent":[17],"features.":[18],"Such":[19,76],"variations":[20],"pose":[21],"considerable":[22],"challenges":[23],"on":[24,40,112],"Cloud":[25],"Service":[26],"Providers":[27],"(CSPs)":[28],"incurred":[29],"the":[31,65,79,87,102,120,124,131,139,147,190,201,213],"fluctuation":[32],"resource":[34],"demands":[35],"along":[36],"their":[38],"impact":[39],"quality":[41],"service":[43],"(QoS)":[44],"optimization.":[45],"Google":[47,125,214],"cluster":[48,126,215],"trace":[49,140],"is":[50,187],"an":[51],"example":[52],"such":[54,157],"wherein":[56],"task":[57],"characteristics":[58,122],"significantly":[59],"differ":[60],"between":[61],"applications,":[62],"which":[63],"makes":[64],"existing":[66],"approaches":[67],"insufficient":[68],"for":[69,81,119,179],"accurate":[70],"predictions":[71],"across":[72],"workload":[74,108,144,184],"scenarios.":[75],"limitations":[77],"emphasize":[78],"need":[80],"a":[82,107],"comprehensive,":[83],"domain\u2010specific":[84],"consideration":[85],"application":[88,105],"deep":[90],"learning":[91,154],"(DL)":[92],"models":[93,156],"to":[94,141,174,206,223],"effectively":[95],"predict":[96,142],"workloads.":[98],"This":[99,217],"paper":[100],"investigates":[101],"design":[103],"prediction":[109,170],"model":[110,129,171,192],"based":[111],"long":[113],"short\u2010term":[114],"memory":[115,210],"(LSTM)":[116],"networks,":[117],"developed":[118],"unique":[121],"trace.":[127,216],"leverages":[130],"LSTM\u2019s":[132],"ability":[133],"capturing":[135],"long\u2010term":[136],"dependencies":[137],"within":[138],"future":[143],"demands,":[145],"extracted":[148],"features":[149],"fed":[150],"into":[151],"machine":[153],"(ML)":[155],"as":[158],"linear":[159],"regression":[160],"(LR),":[161],"K\u2010nearest":[162],"neighbor":[163],"(KNN),":[164],"decision":[166],"tree":[167],"(DT).":[168],"enables":[172],"CSPs":[173],"proactively":[175],"allocate":[176],"sufficient":[177],"resources":[178],"client":[180],"tasks":[181],"optimize":[183],"distribution.":[185],"It":[186],"found":[188],"that":[189],"proposed":[191],"combines":[193],"strengths":[194],"feature":[196],"extraction":[197],"LSTM":[199],"prediction\u2019s":[202],"accuracy":[203],"LR":[205],"forecast":[207],"CPU":[208],"requests":[211],"combination":[218],"demonstrates":[219],"superior":[220],"capabilities":[221],"compared":[222],"convolutional":[224],"neural":[225],"network":[226],"(CNN),":[227],"autoregressive":[228],"integrated":[229],"moving":[230],"average":[231],"(ARIMA),":[232],"extreme":[234],"gradient":[235],"boosting":[236],"(XGBoost)":[237],"models.":[238]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-05-06T00:00:00"}