Performance Aware Egress Path Discovery for Content Provider with SRv6 Egress Peer Engineering

• Published in: IEICE Transactions on Information and Systems Vol. E106.D; no. 5; pp. 927 - 939
• Main Authors: TOYOTA, Yasunobu, MISHIMA, Wataru, KANAYA, Koichiro, NAKAMURA, Osamu
• Format: Journal Article
• Language: English
• Published: Tokyo The Institute of Electronics, Information and Communication Engineers 01.05.2023; Japan Science and Technology Agency
• Subjects: BGP; Data centers; Domains; Egress; egress peer engineering; passive measurement; Quality of service architectures; SRv6; traffic engineering
• ISSN: 0916-8532; 1745-1361
• DOI: 10.1587/transinf.2022NTP0003

QoS of applications is essential for content providers, and it is required to improve the end-to-end communication quality from a content provider to users. Generally, a content provider's data center network is connected to multiple ASes and has multiple egress paths to reach the content user's network. However, on the Internet, the communication quality of network paths outside of the provider's administrative domain is a black box, so multiple egress paths cannot be quantitatively compared. In addition, it is impossible to determine a unique egress path within a network domain because the parameters that affect the QoS of the content are different for each network. We propose a “Performance Aware Egress Path Discovery” method to improve QoS for content providers. The proposed method uses two techniques: Egress Peer Engineering with Segment Routing over IPv6 and Passive End-to-End Measurement. The method is superior in that it allows various metrics depending on the type of content and can be used for measurements without affecting existing systems. To evaluate our method, we deployed the Performance Aware Egress Path Discovery System in an existing content provider network and conducted experiments to provide production services. Our findings from the experiment show that, in this network, 15.9% of users can expect a 30Mbps throughput improvement, and 13.7% of users can expect a 10ms RTT improvement.