A study of massive multidimensional data sharing and interaction algorithms based on cloud-edge collaboration

The current data sharing methods have significant drawbacks in terms of security, efficiency, and scalability. Therefore, this article proposes a massive multi-dimensional data sharing and interaction algorithm based on cloud edge collaboration. In the edge layer and cloud layer, data from sensors and nodes undergo re-encryption through proxies during the collection process. Using the DPoS consensus mechanism for sharing reduces the number of consensus nodes, improves speed and efficiency, and ensures node honesty. The improved DPoS will select proxy nodes. Cloud layers share and access data lake models through smart contracts. The experimental results demonstrate that the algorithm can achieve the sharing and interaction of massive multidimensional data, and the total number of honest nodes in the selected consensus node set reaches over 90%. The consensus process can generate more efficient blocks, which enhances the fault tolerance of data sharing. The study verifies that the method proposed in this article can improve the security of sharing massive multidimensional data.