Performance evaluation of resources management in WebRTC for a scalable communication

Naktal Moaid Edan, Ali Al-Sherbaz, Scott J Turner

Research output: Contribution to Book/ReportChapter


Web Real-Time Communication (WebRTC) offers peer-to-peer communications without any plug-ins. However, WebRTC cannot provide scalability because of its method that depends on a single server or due to the resource limitations and network topology in the architectural of the WebRTC. This paper aims to design a real environment using MATLAB simulation tools to specify the limitations of resources in WebRTC for bi-directional video conferencing, such as CPU performance, bandwidth consumption and Quality of Experience (QoE) using different topologies such as mesh, star and hybrid (a combination of unidirectional/star & bi-directional/mesh). Moreover, several CPU cores like i3, i5, i7, Xeon, i9 and Xeon Phi, as well as bandwidths: 0.5, 1, 5, 10, 30, 50, 100, 500 and 1000 (Mb/s) were considered to achieve and expand the scalability. In this implementation, the factors of real-time implementation were used. Thus, the utilized measurements were already validated while MATLAB presents coefficient with 95% confidence bound. Additionally, this paper highlights the obstructions are preventing scalability in WebRTC using a centralized server. This illustration is beneficial for interested developers who intend to use WebRTC duplex video conferencing among undefined users and different topologies. Furthermore, our simulation-based’ performance evaluation shows the efficiency of the hybrid topology in decreasing the bandwidth overhead and CPU load in WebRTC.
Original languageEnglish
Title of host publicationComputing Conference 2018 Proceedings
Place of PublicationLondon
Publication statusAccepted/In press - 15 Feb 2018


  • The Web Real-Time Communication (WebRTC)
  • Quality of Experience (QoE)
  • mesh topology
  • star topology and hybrid topology

Fingerprint Dive into the research topics of 'Performance evaluation of resources management in WebRTC for a scalable communication'. Together they form a unique fingerprint.

  • Cite this

    Edan, N. M., Al-Sherbaz, A., & Turner, S. J. (Accepted/In press). Performance evaluation of resources management in WebRTC for a scalable communication. In Computing Conference 2018 Proceedings IEEE.