{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/124500"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/124500","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Networking in a heterogeneous world: Optimization, measurement, and opportunities","abstract":"Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2026-05-01","abstract_html":"Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2026-05-01","abstract_has_math":false,"creators":["Chen, Bo-Rong"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"Ph.D.","degree_level":"Dissertation","degree_discipline":"Electrical & Computer Engr","degree_department":null,"school":null,"contributors":["Hu, Yih-Chun","Bailey, Michael","Godfrey, Brighten","Mittal, Radhika"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2024,"date_issued":"2024-05","date_published":"2024-05","updated_at":"2026-07-22T22:25:02Z","subjects":["Internet Bandwidth Management","Content Delivery","End-to-end User Experience","Remote Traffic Shaping","Co-bottleneck Detection","Audience Retention Curve","Youtube","Bilibili"],"languages":["en","eng"],"rights":["Copyright 2024 Bo-Rong Chen"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://hdl.handle.net/2142/124500","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Hu, Yih-Chun","Bailey, Michael","Godfrey, Brighten","Mittal, Radhika"]},{"key":"dc:creator","label":"Author","values":["Chen, Bo-Rong"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2024-05","2024-04-08"]},{"key":"dc:type","label":"Dc Type","values":["text"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Electrical & Computer Engr"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Dissertation"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Ph.D."]},{"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":["Internet Bandwidth Management","Content Delivery","End-to-end User Experience","Remote Traffic Shaping","Co-bottleneck Detection","Audience Retention Curve","Youtube","Bilibili"]}]},{"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 2024 Bo-Rong Chen"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://hdl.handle.net/2142/124500"]}]},{"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 2026-05-01","The student, Bo-Rong Chen, accepted the attached license on 2024-04-02 at 01:35.","The student, Bo-Rong Chen, submitted this Dissertation for approval on 2024-04-02 at 01:37.","This Dissertation was approved for publication on 2024-04-08 at 13:52.","DSpace SAF Submission Ingestion Package generated from Vireo submission #20288 on 2024-09-16 at 00:43:05","Over the past decade, research on video streaming systems has often relied on simplified user studies that fail to capture the diversity and complexity of real-world user behavior, who contribute different economic and social values to content providers. This study seeks to address this oversight by developing and evaluating video streaming systems that aim to enhance provider revenues and take into account the dynamic behaviors of users. First of all, content providers face challenges with delivering content due to bandwidth constraints beyond their control. In this study, we introduce FlowTele, a novel system for optimizing internet traffic through remote traffic shaping, diverging from traditional Transmission Control Protocol (TCP) fairness. FlowTele, designed without the need for in-network or special client support, has shown to enhance providers' revenues by 20%--30% through strategic bandwidth reallocation in various network conditions. Additionally, the research investigates Quality of Experience (QoE) fairness among other metrics that content providers can optimize with FlowTele, offering a solution to bypass bandwidth bottlenecks while maintaining TCP-friendly operations. Secondly, to enhance video streaming quality, adaptive bitrate streaming (ABR) techniques and QoE metrics are utilized. Traditional methods often ignore user interactions like seeking or replaying, leading to a gap in understanding streaming quality. To fill this gap, we collected and analyzed 229,178 audience retention curves from YouTube and Bilibili, which we called vRetention, revealing significant variations in user engagement across different content types and regions. This data aids in refining ABR designs and QoE assessments, offering a deeper insight into user behavior for improved streaming experiences. Finally, evaluating the real-world QoE for ABR is difficult due to traditional evaluations overlooking dynamic user behaviors (e.g., seeking or abandoning videos). This research addresses this by analyzing audience retention curve data and developing mRetention, a dynamic behavior model to assess ABR performance. Findings indicate significant QoE degradation under dynamic behaviors, highlighting issues like overbuffering across network types and insufficient consideration for varied playback speeds."]},{"key":"dc:format","label":"Dc Format","values":["application/pdf"]},{"key":"dc:title","label":"Title","values":["Networking in a heterogeneous world: Optimization, measurement, and opportunities"]}]}],"canonical_facts":{"dc:contributor":["Hu, Yih-Chun","Bailey, Michael","Godfrey, Brighten","Mittal, Radhika"],"dc:creator":["Chen, Bo-Rong"],"dc:date":["2024-05","2024-04-08"],"dc:description":["Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2026-05-01","The student, Bo-Rong Chen, accepted the attached license on 2024-04-02 at 01:35.","The student, Bo-Rong Chen, submitted this Dissertation for approval on 2024-04-02 at 01:37.","This Dissertation was approved for publication on 2024-04-08 at 13:52.","DSpace SAF Submission Ingestion Package generated from Vireo submission #20288 on 2024-09-16 at 00:43:05","Over the past decade, research on video streaming systems has often relied on simplified user studies that fail to capture the diversity and complexity of real-world user behavior, who contribute different economic and social values to content providers. This study seeks to address this oversight by developing and evaluating video streaming systems that aim to enhance provider revenues and take into account the dynamic behaviors of users. First of all, content providers face challenges with delivering content due to bandwidth constraints beyond their control. In this study, we introduce FlowTele, a novel system for optimizing internet traffic through remote traffic shaping, diverging from traditional Transmission Control Protocol (TCP) fairness. FlowTele, designed without the need for in-network or special client support, has shown to enhance providers' revenues by 20%--30% through strategic bandwidth reallocation in various network conditions. Additionally, the research investigates Quality of Experience (QoE) fairness among other metrics that content providers can optimize with FlowTele, offering a solution to bypass bandwidth bottlenecks while maintaining TCP-friendly operations. Secondly, to enhance video streaming quality, adaptive bitrate streaming (ABR) techniques and QoE metrics are utilized. Traditional methods often ignore user interactions like seeking or replaying, leading to a gap in understanding streaming quality. To fill this gap, we collected and analyzed 229,178 audience retention curves from YouTube and Bilibili, which we called vRetention, revealing significant variations in user engagement across different content types and regions. This data aids in refining ABR designs and QoE assessments, offering a deeper insight into user behavior for improved streaming experiences. Finally, evaluating the real-world QoE for ABR is difficult due to traditional evaluations overlooking dynamic user behaviors (e.g., seeking or abandoning videos). This research addresses this by analyzing audience retention curve data and developing mRetention, a dynamic behavior model to assess ABR performance. Findings indicate significant QoE degradation under dynamic behaviors, highlighting issues like overbuffering across network types and insufficient consideration for varied playback speeds."],"dc:format":["application/pdf"],"dc:identifier":["https://hdl.handle.net/2142/124500"],"dc:language":["en","eng"],"dc:rights":["Copyright 2024 Bo-Rong Chen"],"dc:subject":["Internet Bandwidth Management","Content Delivery","End-to-end User Experience","Remote Traffic Shaping","Co-bottleneck Detection","Audience Retention Curve","Youtube","Bilibili"],"dc:title":["Networking in a heterogeneous world: Optimization, measurement, and opportunities"],"dc:type":["text"],"thesis:degree_discipline":["Electrical & Computer Engr"],"thesis:degree_level":["Dissertation"],"thesis:degree_name":["Ph.D."],"thesis:institution_name":["University of Illinois at Urbana-Champaign"]},"updated_at":"2026-07-22T22:25:02Z"}