Robust-DSN - Performance and Fault Tolerance of a Distributed Storage Network

The development of various mobile applications, the Internet of Things (IoT), or smart cities generates massive amounts of data. Cloud computing allows businesses to store, manage, and process data using a network of remote servers hosted on the Internet. However, cloud computing essentially suffers from data security concerns and lack of transparency and trust. Decentralized storage has gained popularity due to fault toler-ance, scalability, privacy, and security properties. However, the widespread adoption of decentralized storage is facing obstacles due to concerns regarding performance and reliability. The need to efficiently schedule tasks from a large and diverse pool of resources is a challenge. In this study, we introduce a robust distributed storage network (Robust-DSN) that leverages the Inter-Planetary File System (IPFS) for content-based data management, Galois Field Arithmetic-based Reed-Solomon encoding for file partitioning, and Particle Swarm Optimization (PSO) for system optimization and lightweight multithreading for concurrent execution of tasks.