Decentralized Cooperative Caching for Web3.0: Framework Design and Latency Optimization

In decentralized architectures of Web3.0, a critical efficiency challenge is that redundant data replication degrades the performance of distributed data access. To address this challenge, we develop a Decentralized Cooperative Caching (DC-Cache) framework for Web3.0. The proposed framework features a two-layer architecture, wherein the Decentralized Oracle Network (DON) layer serves as a trusted intermediary platform for decentralized caching, bridging the contents from decentralized storage and the content requests from users. Targeting the complexity of Web3.0 network topologies and data flows, we propose a Deep Reinforcement Learning-Based Decentralized Caching (DRL-DC) for DC-Cache to dynamically optimize caching strategies of distributed oracles. Experimental results show that, compared with existing caching strategies, DCCache with DRL-DC reduces average access latency by $20 \%$ and increases the cache hit rate by at most $18 \%$.