Abstract
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%.
Highlights
Distributed storage first refers to a storage system built on large-scale and low-cost commercial hardware (networkattached storage (NAS))
This section simplifies the storage cluster topology based on the minimum storage regenerative (MSR) code disaster recovery mechanism represented by ðn, k, dÞ and uses a completely undirected connectivity weight graph G = ðV, E, WÞ to represent the topology structure of the distributed storage system, where V = fv1, v2, ⋯, vng represents the collection of n nodes in the distributed storage system; E = fe1, e2, ⋯, emg, where esð1 ≤ s ≤ mÞ = ðvi, vjÞ represents the links that exist between nodes vi and vj in the topology; and W = fωðvi, vjÞ ∣ ðvi, vj ∈ EÞg represents the available bandwidth on the link and the processing capacity of the vi node itself when vi = vj
To demonstrate the robustness of the repair topology constructed by the proposed method, we analyzed the probability that the repair topology in the MSR code storage cluster with scales of ð10, 6, 8Þ, ð20,12,16Þ, ð40,24,32Þ, and ð80,48,64Þ is reconstructed when nodes in the topology fail during the repair process
Summary
Distributed storage first refers to a storage system built on large-scale and low-cost commercial hardware (networkattached storage (NAS)). In this paper, some nodes with excellent bandwidth properties in the storage cluster are added to the repair node set to participate in the construction of the repair tree as alternative intermediate nodes, and based on the characteristics of the MSR coded intermediate node computation, a Steiner tree model with constraints is established to optimize the repair time delay and the traffic flow in the repair topology. As far as we know, there is no work that considers time delay and robustness at the same time in the available literature we can find (2) The MSR code with better storage characteristics is used to construct an optimal repair tree with constraints based on the calculation of the intermediate nodes, which reduces the repair traffic cost of erasure code tree repair (3) To solve the NP-hard problem of the optimal repair tree, a hybrid genetic algorithm is designed according to the background characteristics of the problem to obtain the optimal repair Steiner tree based on the repair node set.
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