{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/125638"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/125638","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Exploratory research of Lagrangian relaxation for cloud workflow scheduling","abstract":"Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2025-02-04 without embargo terms","abstract_html":"Submission original under an indefinite embargo labeled 'Open Access'. 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The submission was exported from vireo on 2025-02-04 without embargo terms","The student, Yoonhwan Kang, accepted the attached license on 2024-07-15 at 15:16.","The student, Yoonhwan Kang, submitted this Thesis for approval on 2024-07-15 at 15:23.","This Thesis was approved for publication on 2024-07-18 at 08:15.","DSpace SAF Submission Ingestion Package generated from Vireo submission #21120 on 2025-02-04 at 21:05:23","Demand for efficient cloud workflow scheduling solutions is increasing, particularly for managing large-scale datasets. The cloud workflow scheduling problem formulated as a mixed integer linear programming (MILP) problem, requires significant computational time as the dataset scale increases. Consequently, various approaches have been studied to relax the problem into a more solvable form. This thesis presents an exploratory study on applying Lagrangian Relaxation to the cloud workflow scheduling problem. We propose a MILP formulation incorporating moving costs to reflect real-world scenarios better. By applying the Lagrangian relaxation approach and additional methods, we can obtain tight near-optimal solutions quickly. These solutions can serve as lower bounds for the MILP, enabling a reduction in computational time."]},{"key":"dc:format","label":"Dc Format","values":["application/pdf"]},{"key":"dc:title","label":"Title","values":["Exploratory research of Lagrangian relaxation for cloud workflow scheduling"]}]}],"canonical_facts":{"dc:contributor":["Nagi, Rakesh"],"dc:creator":["Kang, Yoonhwan"],"dc:date":["2024-08","2024-07-18"],"dc:description":["Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2025-02-04 without embargo terms","The student, Yoonhwan Kang, accepted the attached license on 2024-07-15 at 15:16.","The student, Yoonhwan Kang, submitted this Thesis for approval on 2024-07-15 at 15:23.","This Thesis was approved for publication on 2024-07-18 at 08:15.","DSpace SAF Submission Ingestion Package generated from Vireo submission #21120 on 2025-02-04 at 21:05:23","Demand for efficient cloud workflow scheduling solutions is increasing, particularly for managing large-scale datasets. The cloud workflow scheduling problem formulated as a mixed integer linear programming (MILP) problem, requires significant computational time as the dataset scale increases. Consequently, various approaches have been studied to relax the problem into a more solvable form. This thesis presents an exploratory study on applying Lagrangian Relaxation to the cloud workflow scheduling problem. We propose a MILP formulation incorporating moving costs to reflect real-world scenarios better. By applying the Lagrangian relaxation approach and additional methods, we can obtain tight near-optimal solutions quickly. These solutions can serve as lower bounds for the MILP, enabling a reduction in computational time."],"dc:format":["application/pdf"],"dc:identifier":["https://hdl.handle.net/2142/125638"],"dc:language":["en","eng"],"dc:rights":["Copyright 2024 Yoonhwan Kang"],"dc:subject":["Cloud Workflow Scheduling","Lagrangian Relaxation (lr)","Gap Closure Theme","Subgradient Method."],"dc:title":["Exploratory research of Lagrangian relaxation for cloud workflow scheduling"],"dc:type":["text","Thesis"],"thesis:degree_discipline":["Industrial Engineering"],"thesis:degree_level":["Thesis"],"thesis:degree_name":["M.S."],"thesis:institution_name":["University of Illinois at Urbana-Champaign"]},"updated_at":"2026-07-22T22:25:02Z"}