{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/120372"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/120372","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Optimized planning for managed wireless network management","abstract":"Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2025-05-01","abstract_html":"Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2025-05-01","abstract_has_math":false,"creators":["Raghunandan, Arpitha"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"M.S.","degree_level":"Thesis","degree_discipline":"Computer Science","degree_department":null,"school":null,"contributors":["Caesar, Matthew"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2023,"date_issued":"2023-05","date_published":"2023-05","updated_at":"2026-07-22T22:24:57Z","subjects":["Managed Wireless Networks","Ran","Ai Planning","Constraint Programming","Management","Synthesis","Sequence Of Actions","Optimization","Modeling"],"languages":["en","eng"],"rights":["Copyright 2023 Arpitha Raghunandan"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://hdl.handle.net/2142/120372","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Caesar, Matthew"]},{"key":"dc:creator","label":"Author","values":["Raghunandan, Arpitha"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2023-05","2023-04-17"]},{"key":"dc:type","label":"Dc Type","values":["text","Thesis"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Computer Science"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Thesis"]},{"key":"thesis:degree_name","label":"Degree Name","values":["M.S."]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Illinois at Urbana-Champaign"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Managed Wireless Networks","Ran","Ai Planning","Constraint Programming","Management","Synthesis","Sequence Of Actions","Optimization","Modeling"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en","eng"]},{"key":"dc:rights","label":"Dc Rights","values":["Copyright 2023 Arpitha Raghunandan"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://hdl.handle.net/2142/120372"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2025-05-01","The student, Arpitha Raghunandan, accepted the attached license on 2023-04-15 at 16:02.","The student, Arpitha Raghunandan, submitted this Thesis for approval on 2023-04-15 at 16:21.","This Thesis was approved for publication on 2023-04-17 at 09:37.","DSpace SAF Submission Ingestion Package generated from Vireo submission #18988 on 2023-09-01 at 17:13:31","A significant majority of modern wireless networks are centralized, composed of a set of base stations operated by a single administrative entity with a wired backhaul, referred to as managed wireless networks. Their underlying infrastructure is growing ever more complex, which in turn makes management tasks difficult. Constituent protocols and systems must work in concert to perform actions, yet may suffer from complex and conflicting interdependencies between management goals and operational steps. Today, operators deal with these challenges through manually maintained playbooks, which contain instructions to be followed when a change to the network is required or observed. However, the instructions in these playbooks, whether automated or human-managed, typically consider management goals individually rather than jointly for optimizing network-wide operations and thus can lead to degraded performance, increased operational expense, and proneness to failure. In this thesis, we explore the possibility of generating an automated playbook to synthesize an optimal sequence of operational steps for efficient management of managed wireless networks while ensuring scalability. We leverage AI-based planning techniques to synthesize efficient system-wide management operations for large-scale managed wireless networks. To improve scalability, (a) we adopt a greedy constraint optimization approach to planning to guide the search process (b) develop compact formal representations of diverse network components and operational actions. We provide concrete use cases of our approach through simulation-based evaluation with Radio Access Networks (RAN), considering some representative management tasks. We find that our approach can compute plans for networks of a few hundred base stations within a few minutes."]},{"key":"dc:format","label":"Dc Format","values":["application/pdf"]},{"key":"dc:title","label":"Title","values":["Optimized planning for managed wireless network management"]}]}],"canonical_facts":{"dc:contributor":["Caesar, Matthew"],"dc:creator":["Raghunandan, Arpitha"],"dc:date":["2023-05","2023-04-17"],"dc:description":["Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2025-05-01","The student, Arpitha Raghunandan, accepted the attached license on 2023-04-15 at 16:02.","The student, Arpitha Raghunandan, submitted this Thesis for approval on 2023-04-15 at 16:21.","This Thesis was approved for publication on 2023-04-17 at 09:37.","DSpace SAF Submission Ingestion Package generated from Vireo submission #18988 on 2023-09-01 at 17:13:31","A significant majority of modern wireless networks are centralized, composed of a set of base stations operated by a single administrative entity with a wired backhaul, referred to as managed wireless networks. Their underlying infrastructure is growing ever more complex, which in turn makes management tasks difficult. Constituent protocols and systems must work in concert to perform actions, yet may suffer from complex and conflicting interdependencies between management goals and operational steps. Today, operators deal with these challenges through manually maintained playbooks, which contain instructions to be followed when a change to the network is required or observed. However, the instructions in these playbooks, whether automated or human-managed, typically consider management goals individually rather than jointly for optimizing network-wide operations and thus can lead to degraded performance, increased operational expense, and proneness to failure. In this thesis, we explore the possibility of generating an automated playbook to synthesize an optimal sequence of operational steps for efficient management of managed wireless networks while ensuring scalability. We leverage AI-based planning techniques to synthesize efficient system-wide management operations for large-scale managed wireless networks. To improve scalability, (a) we adopt a greedy constraint optimization approach to planning to guide the search process (b) develop compact formal representations of diverse network components and operational actions. We provide concrete use cases of our approach through simulation-based evaluation with Radio Access Networks (RAN), considering some representative management tasks. We find that our approach can compute plans for networks of a few hundred base stations within a few minutes."],"dc:format":["application/pdf"],"dc:identifier":["https://hdl.handle.net/2142/120372"],"dc:language":["en","eng"],"dc:rights":["Copyright 2023 Arpitha Raghunandan"],"dc:subject":["Managed Wireless Networks","Ran","Ai Planning","Constraint Programming","Management","Synthesis","Sequence Of Actions","Optimization","Modeling"],"dc:title":["Optimized planning for managed wireless network management"],"dc:type":["text","Thesis"],"thesis:degree_discipline":["Computer Science"],"thesis:degree_level":["Thesis"],"thesis:degree_name":["M.S."],"thesis:institution_name":["University of Illinois at Urbana-Champaign"]},"updated_at":"2026-07-22T22:24:57Z"}