PBE-CC: Congestion Control via Endpoint-Centric, Physical-Layer Bandwidth Measurements

PBE-CC: Congestion Control via Endpoint-Centric, Physical-Layer Bandwidth Measurements
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DOI:
10.1145/3387514.3405880
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发表时间:
2020-02
期刊:
Proceedings of the Annual conference of the ACM Special Interest Group on Data Communication on the applications, technologies, architectures, and protocols for computer communication
影响因子:
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通讯作者:
Yaxiong Xie;Fan Yi;K. Jamieson
Yaxiong Xie;Fan Yi;K. Jamieson
中科院分区:
其他
文献类型:
--
作者:
Yaxiong Xie;Fan Yi;K. Jamieson

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蜂窝网络正变得越来越复杂和拥挤,给当今互联网的端到端网络流带来了最大的延迟、抖动和吞吐量损害。因此,我们主张采用细粒度的基于移动端点的无线测量,通过定义良好的API向移动蜂窝物理层提供精确的拥塞控制算法。我们提出的拥塞控制算法基于在端点(PBE-CC)进行的物理层带宽测量,并捕获了最新的5G新无线电创新,这些创新增加了无线容量,但会造成可用无线容量的突然上升和下降,PBE-CC发送方可以精确和快速地做出反应。我们在软件定义无线电上实现了PBE测量模块的概念验证原型,并在c语言中实现了PBE发送方和接收方。广泛的性能评估将PBE- cc与研究界提出的蜂窝感知和无线无关拥塞控制协议进行了比较,并在部署、移动和静态移动场景以及繁忙和空闲网络中进行了比较。结果表明,平均吞吐量比BBR高6.3%,同时将第95百分位延迟减少1.8倍。
Cellular networks are becoming ever more sophisticated and overcrowded, imposing the most delay, jitter, and throughput damage to end-to-end network flows in today's internet. We therefore argue for fine-grained mobile endpoint-based wireless measurements to inform a precise congestion control algorithm through a well-defined API to the mobile's cellular physical layer. Our proposed congestion control algorithm is based on Physical-Layer Bandwidth measurements taken at the Endpoint (PBE-CC), and captures the latest 5G New Radio innovations that increase wireless capacity, yet create abrupt rises and falls in available wireless capacity that the PBE-CC sender can react to precisely and rapidly. We implement a proof-of-concept prototype of the PBE measurement module on software-defined radios and the PBE sender and receiver in C. An extensive performance evaluation compares PBE-CC head to head against the cellular-aware and wireless-oblivious congestion control protocols proposed in the research community and in deployment, in mobile and static mobile scenarios, and over busy and idle networks. Results show 6.3% higher average throughput than BBR, while simultaneously reducing 95th percentile delay by 1.8x.