Understanding I/O Performance of IPFS Storage: A Client's Perspective

IPFS has surged into popularity in recent years. It organizes user data as multiple objects where users can obtain the objects according to their Content IDentifiers (CIDs). As a storage system, it is of great importance to understand its data I/O performance. But existing work still lacks such a comprehensive study. In this work, we deploy an IPFS storage system with geographically-distributed storage nodes on Amazon EC2. We then conduct extensive experiments to evaluate the performance of data I/O operations from a client's perspective. We find that the access patterns of I/O operations (e.g., request size) severely affect the I/O performance, since IPFS typically uses multiple I/O strategies to perform different I/O requests. Moreover, for the read operations, IPFS requires to resolve remote nodes and downloading objects via the internet. Our experimental study reveals that both resolving and downloading operations can become bottlenecks. Our results can shed light to optimizing IPFS in avoiding high-latency I/O operations.