The rapid growth of Web3.0 is transforming the Internet from a centralized structure to decentralized, which empowers users with unprecedented self-sovereignty over their own data. However, in the context of decentralized data access within Web3.0, it is imperative to cope with efficiency concerns caused by the replication of redundant data, as well as security vulnerabilities caused by data inconsistency. To address these challenges, we develop a Trustworthy Decentralized Cooperative Caching (TDC-Cache) framework for Web3.0 to ensure efficient caching and enhance system resilience against adversarial threats. This 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. In light of the complexity of Web3.0 network topologies and data flows, we propose a Deep Reinforcement Learning-Based Decentralized Caching (DRL-DC) for TDC-Cache to dynamically optimize caching strategies of distributed oracles. Furthermore, we develop a Proof of Cooperative Learning (PoCL) consensus to maintain the consistency of decentralized caching decisions within DON. Experimental results show that, compared with existing approaches, the proposed framework reduces average access latency by 20%, increases the cache hit rate by at most 18%, and improves the average success consensus rate by 10%. Overall, this paper serves as a first foray into the investigation of decentralized caching framework and strategy for Web3.0.

翻译：Web3.0的快速发展正推动互联网从中心化结构向去中心化转型，赋予用户对自身数据前所未有的自主权。然而，在Web3.0的去中心化数据访问场景中，必须应对冗余数据复制导致的效率问题，以及数据不一致引发的安全漏洞。为应对这些挑战，我们开发了一种面向Web3.0的可信去中心化协同缓存（TDC-Cache）框架，以确保高效缓存并增强系统对抗恶意威胁的韧性。该框架采用双层架构，其中去中心化预言机网络（DON）层作为去中心化缓存的可信中介平台，桥接去中心化存储的内容与用户的内容请求。鉴于Web3.0网络拓扑与数据流的复杂性，我们为TDC-Cache提出了一种基于深度强化学习的去中心化缓存（DRL-DC）方法，以动态优化分布式预言机的缓存策略。此外，我们设计了协同学习证明（PoCL）共识机制，以维护DON内去中心化缓存决策的一致性。实验结果表明，与现有方法相比，所提框架将平均访问延迟降低20%，缓存命中率最高提升18%，平均共识成功率提高10%。总体而言，本文首次系统探索了面向Web3.0的去中心化缓存框架与策略。