{"id":{"repo_id":"siu-theses","oai_identifier":"oai:opensiuc.lib.siu.edu:dissertations-2420"},"canonical_url":"https://search.dev.ndltd.org/etd/siu-theses/oai:opensiuc.lib.siu.edu:dissertations-2420","repository":{"repo_id":"siu-theses","name":"Southern Illinois University","base_url":"https://opensiuc.lib.siu.edu/do/oai/"},"display":{"title":"Design and Implementation of Scalable High-Performance Network Functions","abstract":"Service Function Chaining (SFC) enriches the network functionalities to fulfill the increasing demand of value-added services. By leveraging SDN and NFV for SFC, it becomes possible to meet the demand fluctuation and construct a dynamic SFc. However, the integration of SDN with NFV requires packet header modifications, generates excessive network traffics, and induces additional I/O overheads for packet processing. These additional overheads result in a lower system performance, scalability, and agility. To improve the system performance, a co-optimized solution is proposed to implemented NF to achieve a better performance for software-based network functions. To improve the system scalability, a many-field packet classification is proposed to support a more complex ruleset. To improve the system agility, a network function-enabled switch is proposed to lower the network function content switching time. The experiment results show that the performance of a network function is improved by 8 times by leveraging GPU as a parallel computation platform. Moreover, the matching speed to steer network traffics with many-field ruleset is improved by 4 times with the proposed many-field packet classification algorithm. Finally, the proposed system is able to improve system bandwidth 5 times better compared the native solution and maintain the content switch time with the proposed SFC implementation using SDN and NFV.","abstract_html":"Service Function Chaining (SFC) enriches the network functionalities to fulfill the increasing demand of value-added services. By leveraging SDN and NFV for SFC, it becomes possible to meet the demand fluctuation and construct a dynamic SFc. However, the integration of SDN with NFV requires packet header modifications, generates excessive network traffics, and induces additional I/O overheads for packet processing. These additional overheads result in a lower system performance, scalability, and agility. To improve the system performance, a co-optimized solution is proposed to implemented NF to achieve a better performance for software-based network functions. To improve the system scalability, a many-field packet classification is proposed to support a more complex ruleset. To improve the system agility, a network function-enabled switch is proposed to lower the network function content switching time. The experiment results show that the performance of a network function is improved by 8 times by leveraging GPU as a parallel computation platform. Moreover, the matching speed to steer network traffics with many-field ruleset is improved by 4 times with the proposed many-field packet classification algorithm. Finally, the proposed system is able to improve system bandwidth 5 times better compared the native solution and maintain the content switch time with the proposed SFC implementation using SDN and NFV.","abstract_has_math":false,"creators":["Hsieh, Cheng-Liang"],"institution":null,"degree_name":"Doctor of Philosophy","degree_level":"Campus Only Dissertation","degree_discipline":"Electrical and Computer Engineering","degree_department":null,"school":null,"contributors":[],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2017,"date_issued":"2017-08-01T07:00:00Z","date_published":"2017-08-01T07:00:00Z","updated_at":"2026-07-24T04:35:23Z","subjects":["Graphics Processing Unit","Network Function Virtualization","Service Function Chaining","Software-Defined Networking"],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://opensiuc.lib.siu.edu/dissertations/1416","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Hsieh, Cheng-Liang"]},{"key":"dc:creator","label":"Author","values":["Hsieh, Cheng-Liang"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"thesis:degree_discipline","label":"Discipline","values":["Electrical and Computer Engineering"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Campus Only Dissertation"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Doctor of Philosophy"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Graphics Processing Unit","Network Function Virtualization","Service Function Chaining","Software-Defined Networking"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://opensiuc.lib.siu.edu/dissertations/1416"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["Service Function Chaining (SFC) enriches the network functionalities to fulfill the increasing demand of value-added services. By leveraging SDN and NFV for SFC, it becomes possible to meet the demand fluctuation and construct a dynamic SFc. However, the integration of SDN with NFV requires packet header modifications, generates excessive network traffics, and induces additional I/O overheads for packet processing. These additional overheads result in a lower system performance, scalability, and agility. To improve the system performance, a co-optimized solution is proposed to implemented NF to achieve a better performance for software-based network functions. To improve the system scalability, a many-field packet classification is proposed to support a more complex ruleset. To improve the system agility, a network function-enabled switch is proposed to lower the network function content switching time. The experiment results show that the performance of a network function is improved by 8 times by leveraging GPU as a parallel computation platform. Moreover, the matching speed to steer network traffics with many-field ruleset is improved by 4 times with the proposed many-field packet classification algorithm. Finally, the proposed system is able to improve system bandwidth 5 times better compared the native solution and maintain the content switch time with the proposed SFC implementation using SDN and NFV."]},{"key":"dc:title","label":"Title","values":["Design and Implementation of Scalable High-Performance Network Functions"]}]}],"canonical_facts":{"dc:contributor":["Hsieh, Cheng-Liang"],"dc:creator":["Hsieh, Cheng-Liang"],"dc:description.abstract":["Service Function Chaining (SFC) enriches the network functionalities to fulfill the increasing demand of value-added services. By leveraging SDN and NFV for SFC, it becomes possible to meet the demand fluctuation and construct a dynamic SFc. However, the integration of SDN with NFV requires packet header modifications, generates excessive network traffics, and induces additional I/O overheads for packet processing. These additional overheads result in a lower system performance, scalability, and agility. To improve the system performance, a co-optimized solution is proposed to implemented NF to achieve a better performance for software-based network functions. To improve the system scalability, a many-field packet classification is proposed to support a more complex ruleset. To improve the system agility, a network function-enabled switch is proposed to lower the network function content switching time. The experiment results show that the performance of a network function is improved by 8 times by leveraging GPU as a parallel computation platform. Moreover, the matching speed to steer network traffics with many-field ruleset is improved by 4 times with the proposed many-field packet classification algorithm. Finally, the proposed system is able to improve system bandwidth 5 times better compared the native solution and maintain the content switch time with the proposed SFC implementation using SDN and NFV."],"dc:identifier":["https://opensiuc.lib.siu.edu/dissertations/1416"],"dc:subject":["Graphics Processing Unit","Network Function Virtualization","Service Function Chaining","Software-Defined Networking"],"dc:title":["Design and Implementation of Scalable High-Performance Network Functions"],"thesis:degree_discipline":["Electrical and Computer Engineering"],"thesis:degree_level":["Campus Only Dissertation"],"thesis:degree_name":["Doctor of Philosophy"]},"updated_at":"2026-07-24T04:35:23Z"}