A reliable peer-to-peer streaming protocol in low-capacity networks
Autor: | S. O. Ajadi, A.O. Oluwatope, Oluwafolake E. Ojo |
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Rok vydání: | 2020 |
Předmět: |
Live video
Computer Networks and Communications business.industry Computer science Quality of service 020206 networking & telecommunications 02 engineering and technology Peer-to-peer computer.software_genre Network simulation Scheduling (computing) Scalability 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing The Internet Quality of experience business computer Software Computer network |
Zdroj: | Peer-to-Peer Networking and Applications. 14:559-584 |
ISSN: | 1936-6450 1936-6442 |
DOI: | 10.1007/s12083-020-01002-4 |
Popis: | The recent global demand for video streaming applications has paved the way for peer-to-peer streaming system (P2PSS). Strategic scheduling scheme and dynamic overlay topology are essential to maintain quality of service (QoS) and quality of experience (QoE) in P2PSS. The concept of P2PSS was tailored towards relying on active peers’ bandwidth to achieve cheap and scalable means of distribution over the Internet, such that peers with highest bandwidth serve as backbones for others. However, selecting backbone peers in low-capacity network environment is challenging due to insufficient bandwidth and poor infrastructure, thereby resulting in poor QoS and unpleasant user’s QoE. In this paper, we conducted a survey on users’ experiences with live video in selected locations in Nigeria. We designed an adaptive P2P streaming protocol and performed a packet-level simulation in Network Simulator 3(NS-3). Diverse simulation scenarios were set up to evaluate the proposed streaming protocol. Trace files data were analysed to measure end-to-end delay, start-up delay, and throughput. Furthermore, the proposed streaming protocol was benchmarked against selected existing schemes. The evaluation results revealed a 7.4% and 28% reduction in start-up and in end-to-end delays and 9% increase in throughput. |
Databáze: | OpenAIRE |
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