A New Method for Reconstructing Data on a Single Failure Node in the Distributed Storage System Based on the MSR Code

As a storage method for a distributed storage system, an erasure code can save storage space and repair the data of failed nodes. However, most studies that discuss the repair of fault nodes in the erasure code mode only focus on the condition that the bandwidth of heterogeneous links restricts the repair rate but ignore the condition that the storage node is heterogeneous, the cost of repair traffic in the repair process, and the influence of the failure of secondary nodes on the repair process. An optimal repair strategy based on the minimum storage regenerative (MSR) code and a hybrid genetic algorithm is proposed for single-node fault scenarios to solve the above problems. In this work, the single-node data repair problem is modeled as an optimization problem of an optimal Steiner tree with constraints considering heterogeneous link bandwidth and heterogeneous node processing capacity and takes repair traffic and repair delay as optimization objectives. After that, a hybrid genetic algorithm is designed to solve the problem. The experimental results show that under the same scales used in the MSR code cases, our approach has good robustness and its repair delay decreases by 10% and 55% compared with the conventional tree repair topology and star repair topology, respectively; the repair flow increases by 10% compared with the star topology, and the flow rate of the conventional tree repair topology decreases by 40%.