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BLADE: Adaptive Wi-Fi Contention Control for Next-Generation Real-Time Communication

Fengqian Guo, Yuhan Zhou, Longwei Jiang, Congcong Miao, Yuxin Liu, Chenren Xu, Hancheng Lu, Chang Wen Chen, Yaxiong Xie, Honghao Liu

Abstract

Next-generation real-time communication (NGRTC) applications, such as cloud gaming and XR, demand consistently ultra-low latency. However, through our first large-scale measurement, we find that despite the deployment of edge servers, dedicated congestion control, and loss recovery mechanisms, cloud gaming users still experience long-tail latency in Wi-Fi networks. We further identify that Wi-Fi last-mile access points (APs) serve as the primary latency bottleneck. Specifically, short-term packet delivery droughts, caused by fundamental limitations in Wi-Fi contention control standards, are the root cause. To address this issue, we propose BLADE, an adaptive contention control algorithm that dynamically adjusts the contention windows (CW) of all Wi-Fi transmitters based on the channel contention level in a fully distributed manner. Our NS3 simulations and real-world evaluations with commercial Wi-Fi APs demonstrate that, compared to standard contention control, BLADE reduces Wi-Fi packet transmission tail latency by over 5X under heavy channel contention and significantly stabilizes MAC throughput while ensuring fast and fair convergence. Consequently, BLADE reduces the video stall rate in cloud gaming by over 90%.

BLADE: Adaptive Wi-Fi Contention Control for Next-Generation Real-Time Communication

Abstract

Next-generation real-time communication (NGRTC) applications, such as cloud gaming and XR, demand consistently ultra-low latency. However, through our first large-scale measurement, we find that despite the deployment of edge servers, dedicated congestion control, and loss recovery mechanisms, cloud gaming users still experience long-tail latency in Wi-Fi networks. We further identify that Wi-Fi last-mile access points (APs) serve as the primary latency bottleneck. Specifically, short-term packet delivery droughts, caused by fundamental limitations in Wi-Fi contention control standards, are the root cause. To address this issue, we propose BLADE, an adaptive contention control algorithm that dynamically adjusts the contention windows (CW) of all Wi-Fi transmitters based on the channel contention level in a fully distributed manner. Our NS3 simulations and real-world evaluations with commercial Wi-Fi APs demonstrate that, compared to standard contention control, BLADE reduces Wi-Fi packet transmission tail latency by over 5X under heavy channel contention and significantly stabilizes MAC throughput while ensuring fast and fair convergence. Consequently, BLADE reduces the video stall rate in cloud gaming by over 90%.
Paper Structure (64 sections, 22 equations, 31 figures, 6 tables, 1 algorithm)

This paper contains 64 sections, 22 equations, 31 figures, 6 tables, 1 algorithm.

Table of Contents

  1. Introduction
  2. Background
  3. Next-Generation RTC
  4. WLAN Channel Access
  5. Channel via CSMA/CA.
  6. Channel Contention Interval.
  7. Wi-Fi Packet Transmission Procedure.
  8. Wi-Fi MAC Throughput Analysis.
  9. Predictability VS. Efficiency in CSMA
  10. Measurement and Motivation
  11. Large-Scale Online Measurement
  12. Testbed and Data Collection Scheme
  13. Measurement Results
  14. Mechanism Behind Packet Delivery Droughts
  15. Root Cause: Collision-Driven Reactive Contention
  16. ...and 49 more sections

Figures (31)

  • Figure 1: The system architecture of next-generation real-time streaming over wireless LAN.
  • Figure 2: Wi-Fi Frame exchange sequence.
  • Figure 3: Stall rate percentiles in Dec. 2024.
  • Figure 4: Stall rate for 5 GHz Wi-Fi in Dec. 2022 and 2024.
  • Figure 5: Distribution of video frame latency in cloud gaming.
  • ...and 26 more figures