Towards a Software-Defined, Fine-Grained QoS Framework for 5G and Beyond Networks

Towards a Software-Defined, Fine-Grained QoS Framework for 5G and Beyond Networks
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面向 5G 及其他网络的软件定义的细粒度 QoS 框架

DOI:
10.1145/3472727.3472798
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发表时间:
2021
期刊:
NAI'21: Proceedings of the ACM SIGCOMM 2021 Workshop on Network-Application Integration
影响因子:
--
通讯作者:
Salo, Timothy J.
Salo, Timothy J.
中科院分区:
--
文献类型:
--
作者:
Zhang, Zhi-Li;Dayalan, Udhaya Kumar;Ramadan, Eman;Salo, Timothy J.

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5G 提供了大量新特性和功能来支持各种新应用。另一方面,最近对商用 5G 服务的测量研究表明,5G 新无线电(NR),特别是高频段毫米波无线电,也带来了新的挑战。为了有效支持超低延迟和/或高带宽应用等新型应用,我们认为需要真正的跨层网络应用集成,公开应用语义,使 5G 及超 5G (B5G) 网络能够做出智能决策,例如动态无线电资源分配。不幸的是,现有的5G基于流的框架不足以支持这种跨层集成。因此,我们提倡软件定义的细粒度 QoS 框架。我们使用超高分辨率(UHR)体积视频流作为用例,并进行非常初步的实验来证明所提出的框架的潜在好处。这份立场文件作为一个稻草人,呼吁为 B5G 网络和下一代无线系统进行新的智能架构设计。
5G offers a slew of new features and capabilities to support a whole gamut of new applications. On the other hand, 5G new radio (NR), especially, high-band mmWave radio, also poses new challenges, as shown by recent measurement studies of commercial 5G services. In order to effectively support new classes of application such as extra low-latency and/or high-bandwidth applications, we argue that truly cross-layer network-application integration that exposes application semantics to enable 5G and beyond 5G (B5G) networks to make intelligent decisions, e.g., for dynamic radio resource allocation, is needed. Unfortunately the existing 5G flow-based framework is inadequate to support such cross-layer integration. We therefore advocate a software-defined, fine-grained QoS framework. We use ultra-high resolution (UHR) volumetric video streaming as a use case and conduct very preliminary experiments to demonstrate the potential benefits of the proposed framework. This position paper serves as a strawman to call for new intelligent architectural designs for B5G networks and next-generation wireless systems.
DOI: 10.1145/3472771.3474036
发表时间: 2021
期刊: and Use Cases
影响因子: --
作者:
Ramadan, Eman;Narayanan, Arvind;Dayalan, Udhaya Kumar;Fezeu, Rostand A.;Qian, Feng;Zhang, Zhi-Li
通讯作者: Zhang, Zhi-Li
语义感知、面向任务 (SAMO) 网络:应用程序/网络集成框架
DOI: --
发表时间: 2020
期刊: NAI@SIGCOMM
影响因子: --
作者:
T. Salo;Zhi
通讯作者: Zhi