An Optimized Data Storage in A Secure Cloud-Edge Collaboration  A Fault Tolerance Approach

Abstract

The rise of edge smart IoT devices has led to the development of edge storage systems (ESS) for efficient access to massive edge data. ESS can reduce the load on cloud centers and improve user experience. However, ESS still faces challenges in improving fault tolerance and efficiency. Thus, there is a need for a secure and efficient fault-tolerant storage scheme. Existing schemes have drawbacks like high edge storage overhead, difficulty in protecting edge data privacy, and low data writing performance. To address these issues, we propose a Hierarchical Cloud-Edge Collaborative Fault-Tolerant Storage (HCEFT) model. This model aims to enhance system robustness, reduce edge storage overhead, and ensure edge data privacy. We also introduce an optimization method for data writing in HCEFT, called ECWSS (Erasure Code data Writing method based on Steiner tree and SDN). This method improves the trade-off between data writing time and traffic consumption. Our scheme improves data robustness, availability, and security. Additionally, the writing optimization method reduces data write time by 13%-67% and network traffic consumption by 20%-62%, enhancing network load balance performance.