Twitch's CDN as an Open Population Ecosystem.

Wei-Shiang Wung, Guan-Ting Ting,Ruey-Tzer Hsu, Cheng Hsu, Yu-Chien Tsai,Caleb Wang,Yuan-Tai Liu,Hsi Chen,Polly Huang

AINTEC(2021)

引用 1|浏览2
暂无评分
摘要
The quality and continuity of the video services such as Twitch depend on the scale and well-being of their content distribution networks (CDNs). Each CDN may consist of 1000s of servers, physically feeding the videos to the clients. Opting for a better understanding, researchers have attempted to measure and analyze the CDNs of popular video services [10, 11, 12, 19]. These works are, however, one-time effort. Given the widespread use of Twitch, we find continuous survey of its CDN an important subject of study. The challenge lies in the cost of performing the Internet-scale scans – the probing traffic. The larger the CDNs and the more frequent the scans are, the higher the overhead. Instead of performing full scans repeatedly, we envision a cost-effective alternative that samples and estimates the CDN size (i.e., the number of servers). Only when the size change is significant, does the system trigger a full scan. To this end and inspired by Capture-Mark-Recapture (CMR), a methodology widely used in Ecology to estimate animal population with little human effort, we propose two mechanisms to estimate the CDN size with lightweight traffic. Using a data set collected in Nov 2019, we find a 7.25% average estimation error. Provided an estimation error bound, we can identify as well the best parameter combination to minimize the probing traffic.
更多
查看译文
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要