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Towards Low-Latency and Energy-Efficient Hybrid P2P-CDN Live Video Streaming

Reza Farahani, Christian Timmerer, Hermann Hellwagner

TL;DR

The paper addresses rising live video streaming latency and energy concerns by proposing a hybrid P2P-CDN framework that leverages NFV and edge computing. It introduces a four-layer architecture and an action-tree controlled by edge-placed Virtual Tracker Servers to orchestrate fetching and transcoding across peers, VTS, CDN, and origin. A CloudLab-based testbed with 350 DASH clients demonstrates improvements in user QoE, reduced client-serving latency, and lower edge energy consumption relative to baselines. This work shows a viable path to scalable, low-latency, energy-efficient live streaming for OTT providers.

Abstract

Streaming segmented videos over the Hypertext Transfer Protocol (HTTP) is an increasingly popular approach in both live and video-on-demand (VoD) applications. However, designing a scalable and adaptable framework that reduces servers energy consumption and supports low latency and high quality services, particularly for live video streaming scenarios, is still challenging for Over-The-Top (OTT) service providers. To address such challenges, this paper introduces a new hybrid P2P-CDN framework that leverages new networking and computing paradigms, i.e., Network Function Virtualization (NFV) and edge computing for live video streaming. The proposed framework introduces a multi-layer architecture and a tree of possible actions therein (an action tree), taking into account all available resources from peers, edge, and CDN servers to efficiently distribute video fetching and transcoding tasks across a hybrid P2P-CDN network, consequently enhancing the users latency and video quality. We also discuss our testbed designed to validate the framework and compare it with baseline methods. The experimental results indicate that the proposed framework improves user Quality of Experience (QoE), reduces client serving latency, and improves edge server energy consumption compared to baseline approaches.

Towards Low-Latency and Energy-Efficient Hybrid P2P-CDN Live Video Streaming

TL;DR

The paper addresses rising live video streaming latency and energy concerns by proposing a hybrid P2P-CDN framework that leverages NFV and edge computing. It introduces a four-layer architecture and an action-tree controlled by edge-placed Virtual Tracker Servers to orchestrate fetching and transcoding across peers, VTS, CDN, and origin. A CloudLab-based testbed with 350 DASH clients demonstrates improvements in user QoE, reduced client-serving latency, and lower edge energy consumption relative to baselines. This work shows a viable path to scalable, low-latency, energy-efficient live streaming for OTT providers.

Abstract

Streaming segmented videos over the Hypertext Transfer Protocol (HTTP) is an increasingly popular approach in both live and video-on-demand (VoD) applications. However, designing a scalable and adaptable framework that reduces servers energy consumption and supports low latency and high quality services, particularly for live video streaming scenarios, is still challenging for Over-The-Top (OTT) service providers. To address such challenges, this paper introduces a new hybrid P2P-CDN framework that leverages new networking and computing paradigms, i.e., Network Function Virtualization (NFV) and edge computing for live video streaming. The proposed framework introduces a multi-layer architecture and a tree of possible actions therein (an action tree), taking into account all available resources from peers, edge, and CDN servers to efficiently distribute video fetching and transcoding tasks across a hybrid P2P-CDN network, consequently enhancing the users latency and video quality. We also discuss our testbed designed to validate the framework and compare it with baseline methods. The experimental results indicate that the proposed framework improves user Quality of Experience (QoE), reduces client serving latency, and improves edge server energy consumption compared to baseline approaches.
Paper Structure (9 sections, 2 figures, 3 tables)

This paper contains 9 sections, 2 figures, 3 tables.

Table of Contents

  1. Introduction
  2. Motivation
  3. Related Work
  4. Contributions
  5. System Design
  6. Evaluation Setup and Results
  7. Evaluation Setup
  8. Evaluation Results
  9. Conclusion

Figures (2)

  • Figure 1: Proposed multi-layer architecture.
  • Figure 3: Performance of the proposed framework compared with baseline methods in terms of (a) average serving latency, (b) average objective P1203 QoE, (c) average edge server energy consumption for 350 clients running the BOLA and SQUAD ABR algorithms.