{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/113160"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/113160","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Internet congestion control architecture with application-aware utilities and adaptive timescales","abstract":"While the bandwidth of network connectivity has continually increased, the demand for increasingly high quality video, the needs of latency-sensitive interactive applications, and overall increased use of the network have made congestion control a persistently challenging problem. Traditional Internet congestion control primarily divides bandwidth equally among competing flows, but ignores the heterogeneous elasticity, or time sensitivity, in application requirements. In addition, we argue that with the rigid timescale in assessing the performance of different sending rates, existing protocols miss the fundamental opportunity to achieve consistently high performance that can adapt to different network conditions. In this thesis, we first propose PCC Proteus, which accommodates the elasticity in the timing requirements for some applications by developing a scavenger mode for Internet congestion control that yields to normal (primary) flows. Scavenging provides the means for applications with elastic demands to avoid utilizing excessive bandwidth at the expense of those of more immediate priority, thus benefiting users through higher Quality of Experience. Proteus is based on a utility framework, and contains novel utility functions specific to both primary and scavenger priorities. Furthermore, Proteus utilizes a modular architecture, that can flexibly combine the primary and scavenger priorities in a hybrid mode, in which the application can adjust the priority in real-time for enhanced performance. As the first work to comprehensively explore scavenger congestion control, Proteus can both effectively yield to many existing primary protocols and act as a high performance congestion control protocol in general, according to our emulation and real-world evaluation. Second, aimed at introducing adaptability to the timescales in congestion control, we design Rubato. It starts from a pacing scheme encapsulating packet bursts with multiple burst rates, and inherently supports adaptive timescales by leveraging statistical inference techniques. Depending on the network conditions, Rubato is capable of observing the network for multiple RTTs to avoid noisy rate control decisions, and allows sub-RTT timescales with the selection of different burst rates, as well. With a wide range of evaluation, Rubato is shown to achieve a better tradeoff between convergence speed and stability more consistently compared with existing protocols including Proteus. Then, to facilitate real-world adoption, we leverage Proteus's hybrid mode in the adaptive video streaming application. We also port our Proteus and Rubato implementation to QUIC, a widely deployed datapath for transport layer protocols. That experience inspires us with insights on necessary APIs for congestion control implementation.","abstract_html":"While the bandwidth of network connectivity has continually increased, the demand for increasingly high quality video, the needs of latency-sensitive interactive applications, and overall increased use of the network have made congestion control a persistently challenging problem. Traditional Internet congestion control primarily divides bandwidth equally among competing flows, but ignores the heterogeneous elasticity, or time sensitivity, in application requirements. In addition, we argue that with the rigid timescale in assessing the performance of different sending rates, existing protocols miss the fundamental opportunity to achieve consistently high performance that can adapt to different network conditions. In this thesis, we first propose PCC Proteus, which accommodates the elasticity in the timing requirements for some applications by developing a scavenger mode for Internet congestion control that yields to normal (primary) flows. Scavenging provides the means for applications with elastic demands to avoid utilizing excessive bandwidth at the expense of those of more immediate priority, thus benefiting users through higher Quality of Experience. Proteus is based on a utility framework, and contains novel utility functions specific to both primary and scavenger priorities. Furthermore, Proteus utilizes a modular architecture, that can flexibly combine the primary and scavenger priorities in a hybrid mode, in which the application can adjust the priority in real-time for enhanced performance. As the first work to comprehensively explore scavenger congestion control, Proteus can both effectively yield to many existing primary protocols and act as a high performance congestion control protocol in general, according to our emulation and real-world evaluation. Second, aimed at introducing adaptability to the timescales in congestion control, we design Rubato. It starts from a pacing scheme encapsulating packet bursts with multiple burst rates, and inherently supports adaptive timescales by leveraging statistical inference techniques. Depending on the network conditions, Rubato is capable of observing the network for multiple RTTs to avoid noisy rate control decisions, and allows sub-RTT timescales with the selection of different burst rates, as well. With a wide range of evaluation, Rubato is shown to achieve a better tradeoff between convergence speed and stability more consistently compared with existing protocols including Proteus. Then, to facilitate real-world adoption, we leverage Proteus's hybrid mode in the adaptive video streaming application. We also port our Proteus and Rubato implementation to QUIC, a widely deployed datapath for transport layer protocols. That experience inspires us with insights on necessary APIs for congestion control implementation.","abstract_has_math":false,"creators":["Meng, Tong"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"Ph.D.","degree_level":"Dissertation","degree_discipline":"Computer Science","degree_department":null,"school":null,"contributors":["Godfrey, Philip Brighten","Schapira, Michael","Mittal, Radhika","Kravets, Robin Hillary"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2022,"date_issued":"2022-01-12T22:35:06Z","date_published":"2022-01-12T22:35:06Z","updated_at":"2026-07-22T22:24:53Z","subjects":["Transport layer","Congestion control","Scavenger","Adaptive timescale"],"languages":["en"],"rights":["Copyright 2021 Tong Meng"],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/2142/113160","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Godfrey, Philip Brighten","Schapira, Michael","Mittal, Radhika","Kravets, Robin Hillary"]},{"key":"dc:creator","label":"Author","values":["Meng, Tong"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2022-01-12T22:35:06Z","2024-01-12T22:35:30Z","2021-07-09","2021-08"]},{"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":["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":["Transport layer","Congestion control","Scavenger","Adaptive timescale"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["en"]},{"key":"dc:rights","label":"Dc Rights","values":["Copyright 2021 Tong Meng"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["http://hdl.handle.net/2142/113160"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["While the bandwidth of network connectivity has continually increased, the demand for increasingly high quality video, the needs of latency-sensitive interactive applications, and overall increased use of the network have made congestion control a persistently challenging problem. Traditional Internet congestion control primarily divides bandwidth equally among competing flows, but ignores the heterogeneous elasticity, or time sensitivity, in application requirements. In addition, we argue that with the rigid timescale in assessing the performance of different sending rates, existing protocols miss the fundamental opportunity to achieve consistently high performance that can adapt to different network conditions. In this thesis, we first propose PCC Proteus, which accommodates the elasticity in the timing requirements for some applications by developing a scavenger mode for Internet congestion control that yields to normal (primary) flows. Scavenging provides the means for applications with elastic demands to avoid utilizing excessive bandwidth at the expense of those of more immediate priority, thus benefiting users through higher Quality of Experience. Proteus is based on a utility framework, and contains novel utility functions specific to both primary and scavenger priorities. Furthermore, Proteus utilizes a modular architecture, that can flexibly combine the primary and scavenger priorities in a hybrid mode, in which the application can adjust the priority in real-time for enhanced performance. As the first work to comprehensively explore scavenger congestion control, Proteus can both effectively yield to many existing primary protocols and act as a high performance congestion control protocol in general, according to our emulation and real-world evaluation. Second, aimed at introducing adaptability to the timescales in congestion control, we design Rubato. It starts from a pacing scheme encapsulating packet bursts with multiple burst rates, and inherently supports adaptive timescales by leveraging statistical inference techniques. Depending on the network conditions, Rubato is capable of observing the network for multiple RTTs to avoid noisy rate control decisions, and allows sub-RTT timescales with the selection of different burst rates, as well. With a wide range of evaluation, Rubato is shown to achieve a better tradeoff between convergence speed and stability more consistently compared with existing protocols including Proteus. Then, to facilitate real-world adoption, we leverage Proteus's hybrid mode in the adaptive video streaming application. We also port our Proteus and Rubato implementation to QUIC, a widely deployed datapath for transport layer protocols. That experience inspires us with insights on necessary APIs for congestion control implementation.","Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2023-08-01","The student, Tong Meng, accepted the attached license on 2021-07-08 at 18:27.","The student, Tong Meng, submitted this Dissertation for approval on 2021-07-08 at 18:42.","This Dissertation was approved for publication on 2021-07-09 at 11:49.","DSpace SAF Submission Ingestion Package generated from Vireo submission #16812 on 2022-01-12 at 12:54:02","Made available in DSpace on 2022-01-12T22:35:06Z (GMT). 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Traditional Internet congestion control primarily divides bandwidth equally among competing flows, but ignores the heterogeneous elasticity, or time sensitivity, in application requirements. In addition, we argue that with the rigid timescale in assessing the performance of different sending rates, existing protocols miss the fundamental opportunity to achieve consistently high performance that can adapt to different network conditions. In this thesis, we first propose PCC Proteus, which accommodates the elasticity in the timing requirements for some applications by developing a scavenger mode for Internet congestion control that yields to normal (primary) flows. Scavenging provides the means for applications with elastic demands to avoid utilizing excessive bandwidth at the expense of those of more immediate priority, thus benefiting users through higher Quality of Experience. Proteus is based on a utility framework, and contains novel utility functions specific to both primary and scavenger priorities. Furthermore, Proteus utilizes a modular architecture, that can flexibly combine the primary and scavenger priorities in a hybrid mode, in which the application can adjust the priority in real-time for enhanced performance. As the first work to comprehensively explore scavenger congestion control, Proteus can both effectively yield to many existing primary protocols and act as a high performance congestion control protocol in general, according to our emulation and real-world evaluation. Second, aimed at introducing adaptability to the timescales in congestion control, we design Rubato. It starts from a pacing scheme encapsulating packet bursts with multiple burst rates, and inherently supports adaptive timescales by leveraging statistical inference techniques. Depending on the network conditions, Rubato is capable of observing the network for multiple RTTs to avoid noisy rate control decisions, and allows sub-RTT timescales with the selection of different burst rates, as well. With a wide range of evaluation, Rubato is shown to achieve a better tradeoff between convergence speed and stability more consistently compared with existing protocols including Proteus. Then, to facilitate real-world adoption, we leverage Proteus's hybrid mode in the adaptive video streaming application. We also port our Proteus and Rubato implementation to QUIC, a widely deployed datapath for transport layer protocols. That experience inspires us with insights on necessary APIs for congestion control implementation.","Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2023-08-01","The student, Tong Meng, accepted the attached license on 2021-07-08 at 18:27.","The student, Tong Meng, submitted this Dissertation for approval on 2021-07-08 at 18:42.","This Dissertation was approved for publication on 2021-07-09 at 11:49.","DSpace SAF Submission Ingestion Package generated from Vireo submission #16812 on 2022-01-12 at 12:54:02","Made available in DSpace on 2022-01-12T22:35:06Z (GMT). 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