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Container-based load balancing for WebRTC applications

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Published:24 September 2019Publication History

ABSTRACT

Nowadays, the progress of the communication technology is fast. With the popularity of smart phones, tablets and computers, social networking sites or social software have also developed rapidly, changing the user's habit of using network communication software. The demand for streaming audio and video communication has increased dramatically, resulting in the maturity of the Internet today. At present, we can know that there are a variety of applications that can be talked on the market, such as LINE, Skype, Hangouts, etc., which can make instant calls. In the era of the Internet, the communication software has shortened the dispersion in the world. The distance between people everywhere.

This research implements a web-based instant messaging architecture of WebRTC (Web Real-Time Communication, WebRTC) built on a container. We solved the concatenation problem caused by constructing WebRTC services on the container and sought to improve the performance. WebRTC can directly provide instant video and audio communication technology, and cooperate with ICE mechanism to communicate on different domains. No additional Plug-in is needed, only web browser can realize instant messaging function through web browser. It saves a lot of complicated steps, such as: install the user user, and so on. Our system also implements a load balancing mechanism that distributes traffic across the TURN Server, improving overall system performance.

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      • Published in

        cover image ACM Conferences
        RACS '19: Proceedings of the Conference on Research in Adaptive and Convergent Systems
        September 2019
        323 pages
        ISBN:9781450368438
        DOI:10.1145/3338840
        • Conference Chair:
        • Chih-Cheng Hung,
        • General Chair:
        • Qianbin Chen,
        • Program Chairs:
        • Xianzhong Xie,
        • Christian Esposito,
        • Jun Huang,
        • Juw Won Park,
        • Qinghua Zhang

        Copyright © 2019 ACM

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        Association for Computing Machinery

        New York, NY, United States

        Publication History

        • Published: 24 September 2019

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        RACS '19 Paper Acceptance Rate56of188submissions,30%Overall Acceptance Rate393of1,581submissions,25%
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