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Energy-Efficient HTTP Adaptive Streaming System over SDN-Enabled Wi-Fi APs

  • Hyunmin Noh
  • , Gi Seok Park
  • , Yunmin Go
  • , Sang Heon Shin
  • , Youngchan Jang
  • , Hwangjun Song*
  • *Corresponding author for this work
  • Incheon National University
  • Handong Global University
  • Hanwha
  • Pohang University of Science and Technology

Research output: Contribution to journalJournal articlepeer-review

Abstract

This paper presents an energy-efficient Hypertext Transfer Protocol (HTTP) adaptive streaming system to maximize the overall quality of video streaming services for all clients in an energy-efficient way over software-defined networking (SDN)-enabled Wi-Fi access points (APs). To achieve this goal, the proposed system employs multi-path technology to overcome the limitations of a single Wi-Fi AP and adopts the Luby transform (LT) code as forward error correction to support flexible and reliable data transmission via multiple APs. Furthermore, the SDN controller manages the segment bitrate, code rate of the LT code, and video packet transmission via multiple APs based on a global view of the network status, buffer occupancy, and energy consumption. The proposed system is implemented by using network simulator 3 (NS-3) to verify on a large-scale simulation environment and fully implemented in a real testbed to demonstrate its feasibility. The experimental results show that the proposed system can provide superior performance with lower energy consumption than any other existing system.

Original languageEnglish
Pages (from-to)105427-105439
Number of pages13
JournalIEEE Access
Volume11
DOIs
StatePublished - 2023

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 7 - Affordable and Clean Energy
    SDG 7 Affordable and Clean Energy

Keywords

  • Adaptive streaming
  • bitrate adaptation
  • fountain code
  • multi-path
  • segment scheduling
  • software-defined network

Quacquarelli Symonds(QS) Subject Topics

  • Materials Science
  • Computer Science & Information Systems

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