New Infrastructure Aims to Solve Web3’s Memory Challenges
Web3 currently lacks an effective memory layer essential for decentralized computing, which hinders efficiency and scalability. Traditional computing architecture, as outlined by John von Neumann, includes a memory component that Web3 does not replicate adequately.
Key issues include:
- Current blockchain systems use inefficient, ad hoc solutions for data storage and retrieval
- Transactions are slow, costly, and challenging to scale for mass adoption
- The existing data propagation method, known as "gossip," becomes redundant and slow at scale
To address these issues, advancements in memory infrastructure are underway. The MIT-developed Random Linear Network Coding (RLNC) is being utilized to create a decentralized memory system that mimics efficient data handling like RAM in traditional computers. This approach provides:
- Higher throughput and lower latency for data transactions
- Structured, reliable storage, avoiding inefficiencies seen with mempools
- Real-time access and reduced data bloat across the network
Implementing RLNC can solve major bottlenecks in Web3, leading to a more scalable and efficient decentralized ecosystem.