Enhancing Immersive Streaming CDN through MEC-EdgeAI in NG-EPON & 6G-Xhaul Access Network
The integration of Multi-access Edge Computing (MEC) and Edge Artificial Intelligence (EdgeAI) in Next-Generation Passive Optical Networks (NG-EPON) and 6G-Xhaul access networks presents an innovative method to improve immersive live video streaming. EdgeAI offers a potential solution for addressing the quality of service (QoS), dynamic bandwidth management, and reduced latency needs of these contents. The primary motivation behind this research is to enhance the efficiency and performance of Content Delivery Networks (CDNs) when delivering immersive live content. The proposed architecture utilizes Long Short-Term Memory (LSTM) networks to predict bandwidth requirements and dynamically adjust link rates. This ensures the efficient and reliable delivery of immersive live video content with reduced latency. The simulations conducted to evaluate system performance demonstrate substantial improvements in mean packet delay, packet drop probability, and system throughput, thus confirming the effectiveness of the proposed approach.
Authors
- Razat Kharga (ORCID: https://orcid.org/0000-0003-1112-8870)
- I‐Shyan Hwang (ORCID: https://orcid.org/0000-0002-8746-5294)
- Andrew Tanny Liem (ORCID: https://orcid.org/0000-0002-7167-573X)
- AliAkbar Nikoukar (ORCID: https://orcid.org/0000-0001-9056-8000)
Institutions
- Yasouj University (IR)
- Klabat University (ID)
- Yuan Ze University (TW)
Publication Details
- Published
- 2024-10-16
- DOI
- https://doi.org/10.1109/ictc62082.2024.10827178
- Citations
- 1
- Primary Topic
- Advanced Photonic Communication Systems
- Type
- article
- Field-Weighted Citation Impact
- 0.21