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Regional IP Anycast: Deployments, Performance, and Potentials

Publication ,  Conference
Zhou, M; Zhang, X; Hao, S; Yang, X; Zheng, J; Chen, G; Dou, W
Published in: SIGCOMM 2023 - Proceedings of the ACM SIGCOMM 2023 Conference
September 10, 2023

Recent studies show that an end system's traffic may reach a distant anycast site within a global IP anycast system, resulting in high latency. To address this issue, some private and public CDNs have implemented regional IP anycast, a technique that involves dividing content-hosting sites into geographic regions, announcing a unique IP anycast prefix for each region, and utilizing DNS and IP-geolocation to direct clients to CDN sites in their corresponding geographic regions. In this work, we aim to understand how a regional anycast CDN partitions its sites and maps its customers' clients to its sites, and how a regional anycast CDN performs compared to its global anycast counterpart. We study the deployment strategies and the performance of two CDNs (Edgio and Imperva) that currently deploy regional IP anycast. We find that both Edgio and Imperva partition their sites and clients following continent or country borders. Furthermore, we compare the client latency distribution in Imperva's regional anycast CDN with its similar-scale DNS global anycast network, while accounting for and mitigating the relevant deployment differences between the two networks. We find that regional anycast can effectively alleviate the pathology in global IP anycast where BGP routes clients' traffic to distant CDN sites. However, DNS mapping inefficiencies, where DNS returns a sub-optimal regional IP anycast address that does not cover a client's low-latency CDN sites, can harm regional anycast's performance. Finally, we show what performance benefits regional IP anycast can achieve with a latency-based region partition method using the Tangled testbed. When compared to global anycast, regional anycast significantly reduces the 90th percentile client latency by 58.7% to 78.6% for clients across different geographic areas.

Duke Scholars

Published In

SIGCOMM 2023 - Proceedings of the ACM SIGCOMM 2023 Conference

DOI

ISBN

9798400702365

Publication Date

September 10, 2023

Start / End Page

917 / 931
 

Citation

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Zhou, M., Zhang, X., Hao, S., Yang, X., Zheng, J., Chen, G., & Dou, W. (2023). Regional IP Anycast: Deployments, Performance, and Potentials. In SIGCOMM 2023 - Proceedings of the ACM SIGCOMM 2023 Conference (pp. 917–931). https://doi.org/10.1145/3603269.3604846
Zhou, M., X. Zhang, S. Hao, X. Yang, J. Zheng, G. Chen, and W. Dou. “Regional IP Anycast: Deployments, Performance, and Potentials.” In SIGCOMM 2023 - Proceedings of the ACM SIGCOMM 2023 Conference, 917–31, 2023. https://doi.org/10.1145/3603269.3604846.
Zhou M, Zhang X, Hao S, Yang X, Zheng J, Chen G, et al. Regional IP Anycast: Deployments, Performance, and Potentials. In: SIGCOMM 2023 - Proceedings of the ACM SIGCOMM 2023 Conference. 2023. p. 917–31.
Zhou, M., et al. “Regional IP Anycast: Deployments, Performance, and Potentials.” SIGCOMM 2023 - Proceedings of the ACM SIGCOMM 2023 Conference, 2023, pp. 917–31. Scopus, doi:10.1145/3603269.3604846.
Zhou M, Zhang X, Hao S, Yang X, Zheng J, Chen G, Dou W. Regional IP Anycast: Deployments, Performance, and Potentials. SIGCOMM 2023 - Proceedings of the ACM SIGCOMM 2023 Conference. 2023. p. 917–931.

Published In

SIGCOMM 2023 - Proceedings of the ACM SIGCOMM 2023 Conference

DOI

ISBN

9798400702365

Publication Date

September 10, 2023

Start / End Page

917 / 931