{"id":"https://openalex.org/W4390873079","doi":"https://doi.org/10.1109/tsc.2024.3351622","title":"Scheduling Workflow Tasks With Unknown Task Execution Time by Combining Machine-Learning and Greedy-Optimization","display_name":"Scheduling Workflow Tasks With Unknown Task Execution Time by Combining Machine-Learning and Greedy-Optimization","publication_year":2024,"publication_date":"2024-01-15","ids":{"openalex":"https://openalex.org/W4390873079","doi":"https://doi.org/10.1109/tsc.2024.3351622"},"language":"en","primary_location":{"id":"doi:10.1109/tsc.2024.3351622","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsc.2024.3351622","pdf_url":null,"source":{"id":"https://openalex.org/S204223317","display_name":"IEEE Transactions on Services Computing","issn_l":"1939-1374","issn":["1939-1374","2372-0204"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Services Computing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://figshare.com/articles/journal_contribution/Scheduling_workflow_tasks_with_unknown_task_execution_time_by_combining_machine-learning_and_greedy-optimization/26211224","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5044087546","display_name":"Yuanhao Yang","orcid":"https://orcid.org/0000-0002-5007-2139"},"institutions":[{"id":"https://openalex.org/I157773358","display_name":"Sun Yat-sen University","ror":"https://ror.org/0064kty71","country_code":"CN","type":"education","lineage":["https://openalex.org/I157773358"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuanhao Yang","raw_affiliation_strings":["School of Computer Science, Engineering, Sun Yat-sen University, Guangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science, Engineering, Sun Yat-sen University, Guangzhou, China","institution_ids":["https://openalex.org/I157773358"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070128994","display_name":"Hong Shen","orcid":"https://orcid.org/0000-0002-3663-6591"},"institutions":[{"id":"https://openalex.org/I49835588","display_name":"Macao Polytechnic University","ror":"https://ror.org/02sf5td35","country_code":"MO","type":"education","lineage":["https://openalex.org/I49835588"]},{"id":"https://openalex.org/I74899385","display_name":"Central Queensland University","ror":"https://ror.org/023q4bk22","country_code":"AU","type":"education","lineage":["https://openalex.org/I74899385"]}],"countries":["AU","MO"],"is_corresponding":false,"raw_author_name":"Hong Shen","raw_affiliation_strings":["School of Engineering, Technology, Central Queensland University, Brisbane City, QLD, Australia","Faculty of Applied Sciences, Macao Polytechnic University, Macao SAR, China"],"raw_orcid":"https://orcid.org/0000-0002-3663-6591","affiliations":[{"raw_affiliation_string":"School of Engineering, Technology, Central Queensland University, Brisbane City, QLD, Australia","institution_ids":["https://openalex.org/I74899385"]},{"raw_affiliation_string":"Faculty of Applied Sciences, Macao Polytechnic University, Macao SAR, China","institution_ids":["https://openalex.org/I49835588"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100681241","display_name":"Hui Tian","orcid":"https://orcid.org/0000-0002-7952-571X"},"institutions":[{"id":"https://openalex.org/I11701301","display_name":"Griffith University","ror":"https://ror.org/02sc3r913","country_code":"AU","type":"education","lineage":["https://openalex.org/I11701301"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Hui Tian","raw_affiliation_strings":["School of Information, Communication Technology, Griffith University, Southport, QLD, Australia"],"raw_orcid":"https://orcid.org/0000-0002-7952-571X","affiliations":[{"raw_affiliation_string":"School of Information, Communication Technology, Griffith University, Southport, QLD, Australia","institution_ids":["https://openalex.org/I11701301"]}]}],"institutions":[],"countries_distinct_count":3,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":10.2332,"has_fulltext":false,"cited_by_count":16,"citation_normalized_percentile":{"value":0.98026783,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"17","issue":"3","first_page":"1181","last_page":"1195"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10101","display_name":"Cloud Computing and Resource Management","score":0.9972000122070312,"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":0.9972000122070312,"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/T11612","display_name":"Stochastic Gradient Optimization Techniques","score":0.9882000088691711,"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/T10715","display_name":"Distributed and Parallel Computing Systems","score":0.9876999855041504,"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":0.7691898345947266},{"id":"https://openalex.org/keywords/scheduling","display_name":"Scheduling (production processes)","score":0.5023529529571533},{"id":"https://openalex.org/keywords/maximization","display_name":"Maximization","score":0.4879126250743866},{"id":"https://openalex.org/keywords/workflow","display_name":"Workflow","score":0.4299634099006653},{"id":"https://openalex.org/keywords/greedy-algorithm","display_name":"Greedy algorithm","score":0.4228895604610443},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.36082154512405396},{"id":"https://openalex.org/keywords/mathematical-optimization","display_name":"Mathematical optimization","score":0.3540312349796295},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.282881498336792},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.12815406918525696},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.11568909883499146}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7691898345947266},{"id":"https://openalex.org/C206729178","wikidata":"https://www.wikidata.org/wiki/Q2271896","display_name":"Scheduling (production processes)","level":2,"score":0.5023529529571533},{"id":"https://openalex.org/C2776330181","wikidata":"https://www.wikidata.org/wiki/Q18358244","display_name":"Maximization","level":2,"score":0.4879126250743866},{"id":"https://openalex.org/C177212765","wikidata":"https://www.wikidata.org/wiki/Q627335","display_name":"Workflow","level":2,"score":0.4299634099006653},{"id":"https://openalex.org/C51823790","wikidata":"https://www.wikidata.org/wiki/Q504353","display_name":"Greedy algorithm","level":2,"score":0.4228895604610443},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.36082154512405396},{"id":"https://openalex.org/C126255220","wikidata":"https://www.wikidata.org/wiki/Q141495","display_name":"Mathematical optimization","level":1,"score":0.3540312349796295},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.282881498336792},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.12815406918525696},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.11568909883499146}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/tsc.2024.3351622","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tsc.2024.3351622","pdf_url":null,"source":{"id":"https://openalex.org/S204223317","display_name":"IEEE Transactions on Services Computing","issn_l":"1939-1374","issn":["1939-1374","2372-0204"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Services Computing","raw_type":"journal-article"},{"id":"pmh:oai:figshare.com:article/26211224","is_oa":true,"landing_page_url":"https://figshare.com/articles/journal_contribution/Scheduling_workflow_tasks_with_unknown_task_execution_time_by_combining_machine-learning_and_greedy-optimization/26211224","pdf_url":null,"source":{"id":"https://openalex.org/S4377196282","display_name":"Figshare","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210132348","host_organization_name":"Figshare (United Kingdom)","host_organization_lineage":["https://openalex.org/I4210132348"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Text"},{"id":"pmh:oai:research-repository.griffith.edu.au:10072/430659","is_oa":false,"landing_page_url":"https://hdl.handle.net/10072/430659","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"Journal article"}],"best_oa_location":{"id":"pmh:oai:figshare.com:article/26211224","is_oa":true,"landing_page_url":"https://figshare.com/articles/journal_contribution/Scheduling_workflow_tasks_with_unknown_task_execution_time_by_combining_machine-learning_and_greedy-optimization/26211224","pdf_url":null,"source":{"id":"https://openalex.org/S4377196282","display_name":"Figshare","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210132348","host_organization_name":"Figshare (United Kingdom)","host_organization_lineage":["https://openalex.org/I4210132348"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Text"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W2007363252","https://openalex.org/W2052532089","https://openalex.org/W2141992894","https://openalex.org/W2148204686","https://openalex.org/W2165634385","https://openalex.org/W2230700996","https://openalex.org/W2418304172","https://openalex.org/W2916954860","https://openalex.org/W2973989741","https://openalex.org/W3016020363","https://openalex.org/W3109215866","https://openalex.org/W3211228497","https://openalex.org/W6602058072","https://openalex.org/W6631392906","https://openalex.org/W6638161476","https://openalex.org/W6652361255","https://openalex.org/W6657799829","https://openalex.org/W6670624928","https://openalex.org/W6677818966","https://openalex.org/W6681861716","https://openalex.org/W6682147091","https://openalex.org/W6684029880","https://openalex.org/W6684348609","https://openalex.org/W6726877526","https://openalex.org/W6743018549","https://openalex.org/W6755256965","https://openalex.org/W6764508822","https://openalex.org/W6772969002","https://openalex.org/W6773148704"],"related_works":["https://openalex.org/W2891776881","https://openalex.org/W2244559970","https://openalex.org/W2557467218","https://openalex.org/W2536297025","https://openalex.org/W2771290394","https://openalex.org/W2918080139","https://openalex.org/W2389640906","https://openalex.org/W4312077400","https://openalex.org/W2037938733","https://openalex.org/W3130064765"],"abstract_inverted_index":{"Workflow":[0],"tasks":[1,86,114],"are":[2],"time-sensitive":[3,85,113],"and":[4,54,67,90,173,201,251,264],"their":[5,18],"task":[6,12,29,58,92,127],"completion":[7,19,48,220],"utility,":[8],"i.e.,":[9,42],"value":[10],"of":[11,27,36,57,76,106,112,161,191,218,245,272],"completion,":[13],"is":[14,44,62,215],"inversely":[15,45],"proportional":[16,46],"to":[17,23,47,101,125,150],"time.":[20],"Existing":[21],"solutions":[22],"the":[24,34,103,142,147,169,216,232,276],"NP-hard":[25],"problem":[26,239],"utility-maximization":[28],"scheduling":[30,84],"were":[31],"achieved":[32],"under":[33,226],"assumptions":[35],"linear":[37,52,138,208,255],"Time":[38],"Utility":[39],"Function":[40],"(TUF),":[41],"utility":[43,105,153,164,221],"time":[49,94,129],"following":[50],"a":[51,73,110,137,157,242],"function,":[53],"prior":[55],"knowledge":[56],"execution":[59,93,128,175],"time,":[60],"which":[61],"unrealistic":[63],"for":[64,83,198,207,237,248,254],"many":[65],"applications":[66],"dynamic":[68],"systems.":[69],"This":[70],"paper":[71],"proposes":[72],"novel":[74,158],"model":[75],"combining":[77],"greedy":[78,159],"optimization":[79],"with":[80,87,115],"machine":[81],"learning":[82],"convex":[88,199,249],"TUF":[89,200,250,256],"unknown":[91],"on":[95,177],"heterogeneous":[96],"cloud":[97,266],"servers":[98],"offline":[99],"nonpreemptively":[100],"maximize":[102],"total":[104,219,223],"input":[107],"tasks.":[108],"For":[109],"set":[111],"data":[116],"dependencies,":[117],"we":[118,155],"first":[119,233],"employ":[120],"multi-layer":[121],"perceptron":[122],"neural":[123],"networks":[124],"predict":[126],"by":[130,135,146],"utilizing":[131],"historical":[132],"data.":[133],"Then,":[134],"solving":[136],"program":[139],"after":[140],"relaxing":[141],"disjunctive":[143],"constraint":[144],"introduced":[145],"nonpreemption":[148],"requirement":[149],"calculate":[151],"maximum":[152],"increment,":[154],"propose":[156],"algorithm":[160,185,274],"marginal":[162],"incremental":[163],"maximization":[165],"that":[166,183,240],"jointly":[167],"determines":[168],"task-to-processor":[170],"allocation":[171],"plan":[172],"tasks'":[174],"sequence":[176],"each":[178],"processor.":[179],"We":[180],"then":[181],"show":[182],"our":[184,273],"has":[186],"an":[187],"expected":[188],"approximation":[189,235],"ratio":[190,217,247,253],"<inline-formula":[192,202,211],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[193,203,212],"xmlns:xlink=\"http://www.w3.org/1999/xlink\"><tex-math":[194,204,213],"notation=\"LaTeX\">$\\frac{(e-1)(\\tau":[195],"-2)}{e\\tau":[196],"}$</tex-math></inline-formula>":[197],"notation=\"LaTeX\">$\\frac{e-1}{3e}\\approx":[205],"0.21$</tex-math></inline-formula>":[206],"TUF,":[209],"where":[210],"notation=\"LaTeX\">$\\tau$</tex-math></inline-formula>":[214],"over":[222,275],"delay":[224],"cost":[225],"optimal":[227],"scheduling.":[228],"Our":[229],"result":[230],"presents":[231],"polynomial-time":[234],"solution":[236],"this":[238],"achieves":[241],"performance":[243,270],"guarantee":[244],"bounded":[246],"constant":[252],"respectively.":[257],"Extensive":[258],"experiment":[259],"results":[260],"through":[261],"both":[262],"simulation":[263],"real":[265],"implementation":[267],"demonstrate":[268],"significant":[269],"improvement":[271],"known":[277],"results.":[278]},"counts_by_year":[{"year":2026,"cited_by_count":4},{"year":2025,"cited_by_count":10},{"year":2024,"cited_by_count":2}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}