Adaptive Context-Aware Multi-Path Transmission Control for VR/AR Content: A Deep Reinforcement Learning Approach

Shakil Ahmed, Saifur Rahman Sabuj, Ashfaq Khokhar
12/27/2024
cs.NIcs.AI

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Abstract

This paper introduces the Adaptive Context-Aware Multi-Path Transmission Control Protocol (ACMPTCP), an efficient approach designed to optimize the performance of Multi-Path Transmission Control Protocol (MPTCP) for data-intensive applications such as augmented and virtual reality (AR/VR) streaming. ACMPTCP addresses the limitations of conventional MPTCP by leveraging deep reinforcement learning (DRL) for agile end-to-end path management and optimal bandwidth allocation, facilitating path realignment across diverse network environments.

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Cite this paper

@article{ahmed2024adaptive,
  title  = {Adaptive Context-Aware Multi-Path Transmission Control for VR/AR Content: A Deep Reinforcement Learning Approach},
  author = {Shakil Ahmed and Saifur Rahman Sabuj and Ashfaq Khokhar},
  year   = {2024},
  eprint = {2412.19737},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2412.19737v1}
}

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