Guocong Quan
Computer Science · The Ohio State University
Publications
20
Citations
101
Est. group size
~2
Recurring co-author estimate
Active years
10
Publishing since 2017
Guocong Quan's research focuses on caching systems, which are the mechanisms computers and networks use to temporarily store frequently accessed data so it can be retrieved faster. Their work develops mathematical models and algorithms to optimize how content is cached and prefetched at network edges (servers closer to users) in order to reduce delays and operating costs, including analysis of the widely-used LRU (Least Recently Used) caching strategy under various conditions like unreliable connections and shared resources.
Publication output was highest around 2018-2019 and has since slowed to about one paper per year on average over the last five years.
Generated by claude-sonnet-5 from public bibliographic data · Jul 20, 2026
- Optimal Caching for Dynamic Content Through Strategic Information Sharing
2026
- Optimal Edge Caching for Individualized Demand Dynamics
IEEE/ACM Transactions on Networking · 2024
- Minimizing Edge Caching Service Costs Through Regret-Optimal Online Learning
IEEE/ACM Transactions on Networking · 2024
- Optimal Edge Caching For Individualized Demand Dynamics
arXiv (Cornell University) · 2023
- Regret-Optimal Learning for Minimizing Edge Caching Service Costs
2022
- Prefetching and Caching for Minimizing Service Costs
ACM SIGMETRICS Performance Evaluation Review · 2021
- Counterintuitive Characteristics of Optimal Distributed LRU Caching Over Unreliable Channels
IEEE/ACM Transactions on Networking · 2020
- Prefetching and caching for minimizing service costs: Optimal and approximation strategies
Performance Evaluation · 2020
- A New Flexible Multi-flow LRU Cache Management Paradigm for Minimizing Misses
Proceedings of the ACM on Measurement and Analysis of Computing Systems · 2019
- On Resource Pooling and Separation for LRU Caching
ACM SIGMETRICS Performance Evaluation Review · 2019
- A New Flexible Multi-flow LRU Cache Management Paradigm for Minimizing Misses
ACM SIGMETRICS Performance Evaluation Review · 2019
- Counterintuitive Characteristics of Optimal Distributed LRU Caching Over Unreliable Channels
2019
- A New Flexible Multi-flow LRU Cache Management Paradigm for Minimizing Misses
2019
- On Resource Pooling and Separation for LRU Caching
Proceedings of the ACM on Measurement and Analysis of Computing Systems · 2018
- On Resource Pooling and Separation for LRU Caching
ACM SIGMETRICS Performance Evaluation Review · 2018
- ACM SIGMETRICS Performance Evaluation Review×4
- IEEE/ACM Transactions on Networking×3
- arXiv (Cornell University)×3
- Proceedings of the ACM on Measurement and Analysis of Computing Systems×2
- Performance Evaluation×1
- Dongfang Zhao
Computer Science · Indiana University
- Akshat Verma
Computer Science · Purdue University West Lafayette
- Pouya Kousha
Computer Science · The Ohio State University
- Yunqi Zhang
Computer Science · The Ohio State University
- Rubao Lee
Computer Science · The Ohio State University
This profile was generated automatically from public scholarly data (OpenAlex). Group size and activity levels are estimates derived from co-authorship patterns.
Last updated Jul 19, 2026.
Claim or correct this profile