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Minyuan Zhou

dblp:356/8352 · DBLP profile ↗
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5ranked-venue papers
4as first author
5since 2021 · last 2026
0009-0007-3453-0033ORCID · reported

Domains — the database's venue-derived domains; a paper can count in several

Computer networks · 5 · 4 first-author · 5 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer networks
4 papers
Routing and switching · 60% Internet architecture and protocols · 24% Network optimization and economics · 9%

Topics — the 11 heaviest of 11, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Internet architecture and protocols
anycast
2.732026
AnyPro: Preference-Preserving Anycast Optimization based on Strategic AS-Path Prepending · NSDI 2026
ReOpt: Near-Optimal Region Division for Low-Latency Regional Anycast · INFOCOM 2026
Regional IP Anycast: Deployments, Performance, and Potentials · SIGCOMM 2023
Routing and switching › routing › anycast routing
regional anycast
1.722026
ReOpt: Near-Optimal Region Division for Low-Latency Regional Anycast · INFOCOM 2026
Regional IP Anycast: Deployments, Performance, and Potentials · SIGCOMM 2023
Routing and switching › routing
anycast routing
1.012026
ReOpt: Near-Optimal Region Division for Low-Latency Regional Anycast · INFOCOM 2026
Routing and switching › inter-domain routing › BGP
AS-path prepending
1.012026
AnyPro: Preference-Preserving Anycast Optimization based on Strategic AS-Path Prepending · NSDI 2026
Routing and switching › inter-domain routing
BGP
1.012026
AnyPro: Preference-Preserving Anycast Optimization based on Strategic AS-Path Prepending · NSDI 2026
Routing and switching
inter-domain routing
1.012026
AnyPro: Preference-Preserving Anycast Optimization based on Strategic AS-Path Prepending · NSDI 2026
Network optimization and economics
latency optimization
1.012026
ReOpt: Near-Optimal Region Division for Low-Latency Regional Anycast · INFOCOM 2026
Routing and switching › routing protocol
BGP routing policy
0.912025
AnyTuner: Optimizing IP Anycast Performance via Strategic BGP Routing Policy · ICNP 2025
Content delivery and video streaming
content delivery network
0.712023
Regional IP Anycast: Deployments, Performance, and Potentials · SIGCOMM 2023
Network measurement and analytics › latency measurement
round-trip time measurement
0.312025
AnyTuner: Optimizing IP Anycast Performance via Strategic BGP Routing Policy · ICNP 2025
Routing and switching › routing protocol
BGP routing
0.212023
Regional IP Anycast: Deployments, Performance, and Potentials · SIGCOMM 2023

Methods — techniques the papers use, named apart from their topics

strategic AS-path prepending · 1.0neural network · 0.9AS-path prepending · 0.9latency-based region partition · 0.7IP geolocation · 0.7DNS mapping · 0.7
YearPublicationVenuePosition
2026 ReOpt: Near-Optimal Region Division for Low-Latency Regional Anycast
Minyuan Zhou, Congying Wang, Jiaqi Zheng 0001, Shuai Hao 0001, Guihai Chen, Jie Wu 0001
INFOCOM2
2026 AnyPro: Preference-Preserving Anycast Optimization based on Strategic AS-Path Prepending
Minyuan Zhou, Yuning Chen, Jiaqi Zheng 0001, Yongping Tang, Wendong Yin, Qingyan Yu, Yuanchao Su, Guihai Chen, Wan-Chun Dou, Songwu Lu, Wan Du
NSDI1
2026 CDNProbe: Towards accurate and comprehensive CDN identification
Minyuan Zhou, Zixuan Yang 0003, Jiaqi Zheng 0001, Wan-Chun Dou, Guihai Chen
Comput. Networks1
2025 AnyTuner: Optimizing IP Anycast Performance via Strategic BGP Routing Policy
abstract
Optimizing anycast catchment to ensure clients connect to their expected PoPs remains a significant challenge in production networks, primarily due to BGP’s inherent lack of performance awareness. Existing approaches either lack fine-grained routing policy control or prove operationally impractical. In this paper, we present AnyTuner, an automatic route management system that strategically optimizes anycast performance through AS-path prepending and BGP communities. AnyTuner integrates three key components: a measurement-driven optimization loop, a neural network for PoP traffic matrix prediction, and an automated recommendation engine for configuration generation. Deployed for over two years on a commercial cloud platform, AnyTuner demonstrates remarkable efficacy in our evaluation across 18 PoPs and 9,000+ probes, achieving a 39.9% reduction in median RTT (from 36.3 ms to 21.8 ms) compared to policy-free baseline configurations and outperforming state-of-the-art alternatives like AnyOpt by 27.8%.
Minyuan Zhou, Jiaqi Zheng 0001, Congying Wang, Guihai Chen, Wan-Chun Dou
ICNP1
2023 Regional IP Anycast: Deployments, Performance, and Potentials
abstract
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.
Minyuan Zhou, Shuai Hao 0001, Xiaowei Yang 0001, Jiaqi Zheng 0001, Guihai Chen, Wan-Chun Dou
SIGCOMM1