Udhaya Kumar Dayalan, Rostand A. K. Fezeu, T. Salo, Zhi-Li Zhang
{"title":"使用POWDER对5G和NextG网络的细粒度QoS框架进行原型设计","authors":"Udhaya Kumar Dayalan, Rostand A. K. Fezeu, T. Salo, Zhi-Li Zhang","doi":"10.1109/DCOSS54816.2022.00075","DOIUrl":null,"url":null,"abstract":"Unlike previous generation cellular technologies, 5G networks support diverse radio bands from low-band, mid-band to (mmWave) high-band, and offer a wide variety of new and enhanced features. In particular, 3GPP 5G standards adopt a flow-based 5G Quality-of-Service (QoS) framework that allows more flexibility in mapping QoS \"flows\" to data radio bearers. Nonetheless, the 5G QoS classes are pre-defined and QoS treatment is limited to the \"flow\" level. As we will argue in an earlier paper, the 5G QoS framework cannot fully and intelligently utilize the diversity of 5G radio bands and other capabilities to cope with fast varying channel conditions, and is therefore inadequate in meeting the quality-of-experience (QoE) requirements of many emerging applications such as augmented/virtual realities (AR/VR) and connected and autonomous vehicles (CAV). This has led us to advance a novel software-defined, fine-grained QoS framework for 5G/NextG networks.In this \"work in progress\" paper, we share our initial experience in prototyping the proposed fine-grained QoS framework. Our framework extends both the 5G core network and 5G radio access network (RAN) functionality to enable intelligent control of radio resources in a fashion that exploits application semantics to improve user QoE. We discuss in detail about the changes in different systems and its individual components, share the current state of implementation progress (work completed and in-progress) and finally our evaluation plan to validate the framework when the implementation is complete.","PeriodicalId":300416,"journal":{"name":"2022 18th International Conference on Distributed Computing in Sensor Systems (DCOSS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Prototyping a Fine-Grained QoS Framework for 5G and NextG Networks using POWDER\",\"authors\":\"Udhaya Kumar Dayalan, Rostand A. K. Fezeu, T. Salo, Zhi-Li Zhang\",\"doi\":\"10.1109/DCOSS54816.2022.00075\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Unlike previous generation cellular technologies, 5G networks support diverse radio bands from low-band, mid-band to (mmWave) high-band, and offer a wide variety of new and enhanced features. In particular, 3GPP 5G standards adopt a flow-based 5G Quality-of-Service (QoS) framework that allows more flexibility in mapping QoS \\\"flows\\\" to data radio bearers. Nonetheless, the 5G QoS classes are pre-defined and QoS treatment is limited to the \\\"flow\\\" level. As we will argue in an earlier paper, the 5G QoS framework cannot fully and intelligently utilize the diversity of 5G radio bands and other capabilities to cope with fast varying channel conditions, and is therefore inadequate in meeting the quality-of-experience (QoE) requirements of many emerging applications such as augmented/virtual realities (AR/VR) and connected and autonomous vehicles (CAV). This has led us to advance a novel software-defined, fine-grained QoS framework for 5G/NextG networks.In this \\\"work in progress\\\" paper, we share our initial experience in prototyping the proposed fine-grained QoS framework. Our framework extends both the 5G core network and 5G radio access network (RAN) functionality to enable intelligent control of radio resources in a fashion that exploits application semantics to improve user QoE. 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Prototyping a Fine-Grained QoS Framework for 5G and NextG Networks using POWDER
Unlike previous generation cellular technologies, 5G networks support diverse radio bands from low-band, mid-band to (mmWave) high-band, and offer a wide variety of new and enhanced features. In particular, 3GPP 5G standards adopt a flow-based 5G Quality-of-Service (QoS) framework that allows more flexibility in mapping QoS "flows" to data radio bearers. Nonetheless, the 5G QoS classes are pre-defined and QoS treatment is limited to the "flow" level. As we will argue in an earlier paper, the 5G QoS framework cannot fully and intelligently utilize the diversity of 5G radio bands and other capabilities to cope with fast varying channel conditions, and is therefore inadequate in meeting the quality-of-experience (QoE) requirements of many emerging applications such as augmented/virtual realities (AR/VR) and connected and autonomous vehicles (CAV). This has led us to advance a novel software-defined, fine-grained QoS framework for 5G/NextG networks.In this "work in progress" paper, we share our initial experience in prototyping the proposed fine-grained QoS framework. Our framework extends both the 5G core network and 5G radio access network (RAN) functionality to enable intelligent control of radio resources in a fashion that exploits application semantics to improve user QoE. We discuss in detail about the changes in different systems and its individual components, share the current state of implementation progress (work completed and in-progress) and finally our evaluation plan to validate the framework when the implementation is complete.