Learning Relaxed Belady for Content Distribution Network Caching
Explore a groundbreaking approach to content distribution network caching in this 20-minute USENIX NSDI '20 conference talk. Dive into the Learning Relaxed Belady (LRB) algorithm, which uses machine learning to approximate the Belady MIN algorithm for improved caching performance. Discover the innovative concepts of the Relaxed Belady algorithm, Belady boundary, and good decision ratio. Learn how LRB addresses system challenges in implementing machine learning for caching, including data collection, memory management, and efficient training and inference. Examine the results of LRB simulations using production CDN traces, showcasing significant reductions in WAN traffic compared to typical CDN cache designs. Gain insights into the practical implementation of LRB within Apache Traffic Server and its potential for deployment on current CDN servers.