The file system metadata service is the scalability bottleneck for many of today’s workloads. Common approaches for attacking this “metadata scaling wall” include: caching inodes on clients and servers, caching parent inodes for path traversal, and …
When data grows too large, we scale to larger systems, either by scaling out or up. It is understood that scale-out and scale-up have different complexities and bottlenecks but a thorough comparison of the two architectures is challenging because of …
Many applications---for example, scientific simulation, real-time data acquisition, and distributed reservation systems---have I/O performance requirements, yet most large, distributed storage systems lack the ability to guarantee I/O performance. We …