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

Shakil Ahmed; Saifur Rahman Sabuj; Ashfaq Khokhar

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arXiv · 2412.19737

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

Shakil Ahmed·Saifur Rahman Sabuj·Ashfaq Khokhar

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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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BibTeX RIS

Shakil Ahmed, Saifur Rahman Sabuj, Ashfaq Khokhar. 2024-12-27. Adaptive Context-Aware Multi-Path Transmission Control for VR/AR Content: A Deep Reinforcement Learning Approach. https://arxiv.org/abs/2412.19737

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