Blockchain-assisted caching optimization and data storage methods in edge environment

With the rapid advancement of communication technology in the Internet of Things, a slew of new technologies and applications, such as virtual reality and augmented reality, are developing, placing greater demands on transmission latency and storage capacity. As a newly developed compute architecture, edge computing can serve applications that require low latency and high bandwidth better. By sinking cloud computing capabilities to the user side, edge computing collaborates with the cloud and terminals to achieve controlled processing of massive data. Therefore, in order to cache data that meets user requirements better, this paper proposed a blockchain-assisted caching optimization model and data storage method in the edge environment. In this model, factors such as base station location selection and cache content prediction are considered, with the aim of maximizing the quality of service and user interest. During the experiments of caching optimization, when Zipf is 0.5 and other factors remain constant, the proposed algorithm has an average cache hit rate of 4.22%, 11.03%, 19.34%, and 32.35% higher than the JSCCO algorithm, EETCO algorithm, DPCP algorithm, and RR algorithm, respectively. In terms of data storage, when the storage size of the file is 32 MB and other aspects stay constant, the storage time of the proposed method is 16.26%, 16.94%, and 31.56% lower than the IDFS method, EDDS method, and IISM method, respectively.