C2DN: How to Harness Erasure Codes at the Edge for Efficient Content Delivery
Juncheng Yang, Anirudh Sabnis, Daniel S. Berger, K. V. Rashmi, Ramesh K. Sitaraman
Abstract
Content Delivery Networks (CDNs) deliver much of the world's web and video content to users from thousands of clusters deployed at the "edges" of the Internet. Maintaining consistent performance in this large distributed system is challenging. Through analysis of month-long logs from over 2000 clusters of a large CDN, we study the patterns of server unavailability. For a CDN with no redundancy, each server unavailability causes a sudden loss in performance as the objects previously cached on that server are not accessible, which leads to a miss ratio spike. The state-of-the-art mitigation technique used by large CDNs is to replicate objects across multiple servers within a cluster. We find that although replication reduces miss ratio spikes, spikes remain a performance challenge. We present C2DN, the first CDN design that achieves a lower miss ratio, higher availability, higher resource efficiency, and close-to-perfect write load balancing. The core of our design is to introduce erasure coding into the CDN architecture and use the parity chunks to re-balance the write load across servers. We implement C2DN on top of open-source production software and demonstrate that compared to replication-based CDNs, C2DN obtains 11% lower byte miss ratio, eliminates unavailability-induced miss ratio spikes, and reduces write load imbalance by 99%.
Ask about this paper
Your agent reads all of it.
Lune indexed this paper to the last equation, along with the top-tier papers that cite it. Ask a question and the answer quotes them.
Your agent calls
Luneget_paper_fulltext
Free to start. No credit card required.
Terminal
Install the CLIlune papers fulltext 086c62bc-47fe-403e-8eef-ea01c50cf46cCited by top-tier papers11
- SIEVE is Simpler than LRU: an Efficient Turn-Key Eviction Algorithm for Web CachesYazhuo Zhang, Juncheng Yang, Yao Yue, Ymir Vigfusson et al.NSDI 2024 · 63 citations
- GL-Cache: Group-level learning for efficient and high-performance cachingJuncheng Yang, Ziming Mao, Yao Yue, K. V. RashmiFAST 2023 · 60 citations
- FIFO queues are all you need for cache evictionJuncheng Yang, Yazhuo Zhang, Ziyue Qiu, Yao Yue et al.SOSP 2023 · 54 citations
- FrozenHot Cache: Rethinking Cache Management for Modern HardwareZiyue Qiu, Juncheng Yang, Juncheng Zhang, Cheng Li et al.EuroSys 2023 · 33 citations
- Enhancing Resource Management of the World's Largest PCDN System for On-Demand Video StreamingRuixiao Zhang, Haiping Wang, Shu Shi, Xiaofei Pang et al.USENIX ATC 2024 · 25 citations
Builds on7
- A large scale analysis of hundreds of in-memory cache clusters at TwitterJuncheng Yang, Yao Yue, K. V. RashmiOSDI 2020 · 245 citations
- The CacheLib Caching Engine: Design and Experiences at ScaleBenjamin Berg, Daniel S. Berger, Sara McAllister, Isaac Grosof et al.OSDI 2020 · 145 citations
- Segcache: a memory-efficient and scalable in-memory key-value cache for small objectsJuncheng Yang, Yao Yue, Rashmi VinayakNSDI 2021 · 70 citations
- Akamai DNS: Providing Authoritative Answers to the World's QueriesKyle Schomp, Onkar Bhardwaj, Eymen Kurdoglu, Mashooq Muhaimen et al.SIGCOMM 2020 · 38 citations
- Kangaroo: Caching Billions of Tiny Objects on FlashSara McAllister, Benjamin Berg, Julian Tutuncu-Macias, Juncheng Yang et al.SOSP 2021 · 38 citations
Related papers
- PDL: A Data Layout towards Fast Failure Recovery for Erasure-coded Distributed Storage SystemsLiangliang Xu, Min Lv, Zhipeng Li, Cheng Li et al.INFOCOM 2020 · 13 citations
- Midgress-aware traffic provisioning for content deliveryAditya Sundarrajan, Mangesh Kasbekar, Ramesh K. Sitaraman, Samta ShuklaUSENIX ATC 2020 · 22 citations
- RLive: Robust Delivery System for Scaling Live Streaming ServicesYu Tian, Gerui Lv, Qinghua Wu, Ruili Fang et al.EuroSys 2026
- Exploiting Combined Locality for Wide-Stripe Erasure Coding in Distributed StorageYuchong Hu, Liangfeng Cheng, Qiaori Yao, Patrick P. C. Lee et al.FAST 2021 · 88 citations
- Web-LEGO: Trading Content Strictness for Faster WebpagesPengfei Wang, Matteo Varvello, Chunhe Ni, Ruiyun Yu et al.INFOCOM 2021 · 4 citations
