PCC 优先级:QUIC 的优先级感知带宽分配框架

Zhuoyue Chen;Kechao Cai;Jinbei Zhang;Xiangwei Zhu
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引用次数: 0

摘要

当前版本的 QUIC(Quick UDP Internet Connection,快速 UDP 互联网连接)不允许为多个数据流优先分配带宽。在这封信中,我们提出了一个新框架--面向性能的拥塞控制优先级(PCC Priority),以支持 QUIC 流的优先级感知带宽分配。我们的框架将流优先级纳入 PCC 的效用函数,从而根据流优先级按比例分配带宽。我们还提供了 PCC 优先级的均衡分析,并证明它能根据流优先级按比例分配带宽。我们的 ns-3 仿真结果表明,PCC 优先级在遵循 QUIC 中流的优先级设置方面优于最先进的协议。特别是,PCC 优先级以接近流优先级比例的比率为流分配带宽,并保持了有竞争力的高吞吐量、低延迟和高损失容限。
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PCC Priority: A Priority-Aware Bandwidth Allocation Framework for QUIC
The current version of QUIC (Quick UDP Internet Connection) does not allow for prioritized bandwidth allocation of multiple streams. In this letter, we propose a novel framework, Performance-oriented Congestion Control Priority (PCC Priority), to support priority-aware bandwidth allocation of QUIC streams. Our framework incorporates stream priorities into the utility function of PCC to allocate bandwidth proportionally according to the stream priorities. We also provide an equilibrium analysis of PCC Priority and prove that it can allocate bandwidth proportionally based on stream priorities. Our ns-3 simulation results show that PCC Priority outperforms the state-of-the-art protocols in adhering to the priority settings of streams in QUIC. In particular, PCC Priority allocates bandwidth to streams at a ratio that is close to the ratio of their priorities and maintains competitive high throughput, low latency, and high loss tolerance.
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Table of Contents IEEE Networking Letters Author Guidelines IEEE COMMUNICATIONS SOCIETY IEEE Communications Society Optimal Classifier for an ML-Assisted Resource Allocation in Wireless Communications
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