{"id":"https://openalex.org/W7225834169","doi":"https://doi.org/10.48550/arxiv.2611.13740","title":"Multi-Objective Scheduling of LLM-Based Multi-Agent Workflows in Cloud Computing","display_name":"Multi-Objective Scheduling of LLM-Based Multi-Agent Workflows in Cloud Computing","publication_year":2026,"publication_date":"2026-11-10","ids":{"openalex":"https://openalex.org/W7225834169","doi":"https://doi.org/10.48550/arxiv.2611.13740"},"language":"en","primary_location":{"id":"doi:10.48550/arxiv.2611.13740","doi":"https://doi.org/10.48550/arxiv.2611.13740","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2611.13740","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"volume":null,"type":"preprint","is_traditional":true,"indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2611.13740","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5065796961","display_name":"Goshgar Can Ismayilov","orcid":"https://orcid.org/0009-0007-9307-3637","observed_orcids":["https://orcid.org/0009-0007-9307-3637"]},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Ismayilov, Goshgar Can","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":["https://openalex.org/A5065796961"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"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":0.9140999913215637,"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":0.9140999913215637,"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/T10551","display_name":"Scheduling and Optimization Algorithms","score":0.035599999129772186,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10715","display_name":"Distributed and Parallel Computing Systems","score":0.03420000150799751,"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":[],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8203999996185303},{"id":"https://openalex.org/C79974875","wikidata":"https://www.wikidata.org/wiki/Q483639","display_name":"Cloud computing","level":2,"score":0.7731999754905701},{"id":"https://openalex.org/C177212765","wikidata":"https://www.wikidata.org/wiki/Q627335","display_name":"Workflow","level":2,"score":0.692300021648407},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.6793000102043152},{"id":"https://openalex.org/C206729178","wikidata":"https://www.wikidata.org/wiki/Q2271896","display_name":"Scheduling (production processes)","level":2,"score":0.5940999984741211},{"id":"https://openalex.org/C172191483","wikidata":"https://www.wikidata.org/wiki/Q1071806","display_name":"Provisioning","level":2,"score":0.5703999996185303},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.5378999710083008},{"id":"https://openalex.org/C55416958","wikidata":"https://www.wikidata.org/wiki/Q6206757","display_name":"Job shop scheduling","level":3,"score":0.45500001311302185},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.43720000982284546},{"id":"https://openalex.org/C107568181","wikidata":"https://www.wikidata.org/wiki/Q5319000","display_name":"Dynamic priority scheduling","level":3,"score":0.3928999900817871},{"id":"https://openalex.org/C31689143","wikidata":"https://www.wikidata.org/wiki/Q733809","display_name":"Fair-share scheduling","level":3,"score":0.3109000027179718},{"id":"https://openalex.org/C140824633","wikidata":"https://www.wikidata.org/wiki/Q2808660","display_name":"Workflow management system","level":3,"score":0.2971000075340271},{"id":"https://openalex.org/C5119721","wikidata":"https://www.wikidata.org/wiki/Q220501","display_name":"Quality of service","level":2,"score":0.2969000041484833},{"id":"https://openalex.org/C2781055072","wikidata":"https://www.wikidata.org/wiki/Q25325266","display_name":"Cloudlet","level":3,"score":0.28360000252723694},{"id":"https://openalex.org/C137836250","wikidata":"https://www.wikidata.org/wiki/Q984063","display_name":"Optimization problem","level":2,"score":0.25859999656677246},{"id":"https://openalex.org/C206345919","wikidata":"https://www.wikidata.org/wiki/Q20380951","display_name":"Resource (disambiguation)","level":2,"score":0.25690001249313354}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2611.13740","doi":"https://doi.org/10.48550/arxiv.2611.13740","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2611.13740","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2611.13740","doi":"https://doi.org/10.48550/arxiv.2611.13740","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2611.13740","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Large":[0],"language":[1],"models":[2,20,50],"(LLMs)":[3],"have":[4],"been":[5],"increasingly":[6,80],"composed":[7],"into":[8],"multi-agent":[9,127],"workflows":[10],"to":[11,22,63,207],"accomplish":[12],"complex":[13],"and":[14,68,92,119,141,189,204,217,225],"multi-step":[15],"tasks.":[16],"As":[17],"the":[18,24,28,43,59,75,196,199,230,238],"open-weight":[19],"continue":[21],"close":[23],"performance":[25],"gap":[26],"with":[27,61,169,233],"proprietary":[29],"ones,":[30],"model":[31],"parameters":[32],"are":[33,51],"becoming":[34],"a":[35,133,162,180,190],"less":[36],"significant":[37],"source":[38],"of":[39,104,113,156,183,213,219],"competitive":[40],"advantage":[41],"in":[42,74,129,159],"artificial":[44],"intelligence":[45],"market.":[46],"Yet":[47],"how":[48],"these":[49],"efficiently":[52],"scheduled":[53],"onto":[54],"distributed":[55],"infrastructure":[56],"such":[57,107],"as":[58,108,132],"cloud,":[60],"respect":[62],"overall":[64,210],"latency,":[65,110],"monetary":[66],"cost":[67,142],"resource":[69,120,145,223],"utilization,":[70],"remains":[71],"largely":[72],"unaddressed":[73],"literature":[76],"despite":[77],"being":[78],"an":[79],"critical":[81],"problem.":[82],"Existing":[83],"agentic":[84],"workflow":[85,200,220],"frameworks":[86],"mostly":[87],"focus":[88],"on":[89,148],"output":[90],"quality":[91,212],"task":[93],"success":[94],"rates":[95],"over":[96],"popular":[97],"benchmarks,":[98],"rarely":[99],"accounting":[100],"for":[101],"execution":[102],"dynamics":[103],"LLM-based":[105],"agents":[106],"inference":[109],"computation":[111],"power":[112],"heterogeneous":[114],"resources,":[115],"cloud-specific":[116],"billing":[117],"period":[118],"provisioning":[121],"overheads.":[122],"Therefore,":[123],"this":[124,149],"paper":[125],"formulates":[126],"scheduling":[128,163],"cloud":[130,222],"computing":[131],"multi-objective":[134,167,181,202],"optimization":[135,203],"problem":[136],"that":[137],"jointly":[138],"minimizes":[139],"makespan":[140],"while":[143],"maximizing":[144],"utilization.":[146],"Building":[147],"formulation,":[150],"we":[151],"propose":[152],"MO-SAIC":[153],"(Multi-Objective":[154],"Scheduling":[155],"Multi-Agent":[157],"Workflows":[158],"Cloud":[160],"Computing),":[161],"framework":[164],"comprising":[165],"four":[166],"schedulers":[168,197],"Non-Dominated":[170],"Sorting":[171],"Genetic":[172,177],"Algorithm":[173,178],"II":[174],"(NSGA-II),":[175],"Weighted-Sum":[176],"(W-GA),":[179],"adaptation":[182],"Heterogeneous":[184],"Earliest":[185],"Finish":[186],"Time":[187],"(MO-HEFT)":[188],"random":[191],"baseline":[192],"(RAND).":[193],"We":[194,228],"evaluate":[195],"from":[198],"scheduling,":[201],"system":[205],"perspectives":[206],"measure":[208],"their":[209,214,234],"performance,":[211],"Pareto-optimal":[215],"fronts":[216],"impacts":[218],"topology,":[221],"composition":[224],"scalability":[226],"parameters.":[227],"report":[229],"experimental":[231],"results":[232],"statistical":[235],"significance":[236],"via":[237],"Wilcoxon":[239],"test.":[240]},"counts_by_year":[],"updated_date":"2026-11-12T12:28:57.059296","created_date":"2026-11-12T00:00:00"}