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Dynamic multiple node failure recovery in distributed storage systems

机译：分布式存储系统中的动态多节点故障恢复

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Our daily lives are getting more and more dependent on data centers and distributed storage systems in general, whether at the business or at the personal level. With the advent of fog computing, personal mobile devices in a given geographical area may also comprise a very dynamic distributed storage system. These paradigm changes call for the urgent need of devising efficient and reliable failure recovery mechanisms in dynamic scenarios where failures become more likely and nodes join and leave the network more frequently. Redundancy schemes in distributed storage systems have become essential for providing reliability given the fact of frequent node failures. In this work, we address the problem of multiple failure recovery with dynamic scenarios using the fractional repetition code as a redundancy scheme. The fractional repetition (FR) code is a class of regenerating codes that concatenates a maximum distance separable code (MDS) with an inner fractional repetition code where data is split into several blocks then replicated and multiple replicas of each block are stored on various system nodes. We formulate the problem as an integer linear programming problem and extend it to account for three dynamic scenarios of newly arriving blocks, nodes, and variable priority blocks allocation. The contribution of this paper is four-fold: i. we generate an optimized block distribution scheme that minimizes the total system repair cost of all dependent and independent multiple node failure scenarios; ii. we address the practical scenario of having newly arriving blocks and allocate those blocks to existing nodes without any modification to the original on-node block distribution; iii. we consider new-comer nodes and generate an updated optimized block distribution; iv. we consider optimized storage and recovery of blocks with varying priority using variable fractional repetition codes. The four problems are modeled using incidence matrices and solved heuristically. We present a range of results for our proposed algorithms in several scenarios to assess the effectiveness of the solution approaches that are shown to generate results close to optimal. (C) 2017 Published by Elsevier B.V.
机译：总体而言，无论是在企业还是个人层面上，我们的日常生活越来越依赖于数据中心和分布式存储系统。随着雾计算的出现，给定地理区域中的个人移动设备也可能包括一个非常动态的分布式存储系统。这些范式的变化迫切需要在动态情况下设计高效且可靠的故障恢复机制，在这种动态情况下，故障发生的可能性更高，节点加入和离开网络的频率更高。鉴于频繁发生节点故障的事实，分布式存储系统中的冗余方案对于提供可靠性已变得至关重要。在这项工作中，我们使用分数重复代码作为冗余方案解决了动态场景下的多故障恢复问题。分数重复（FR）码是一类再生代码，它将最大距离可分离码（MDS）与内部分数重复码连接在一起，其中数据被拆分成几个块，然后被复制，每个块的多个副本存储在各个系统节点上。我们将该问题表述为整数线性规划问题，并将其扩展为解决新到达的块，节点和可变优先级块分配的三种动态情况。本文的贡献有四个方面：i。我们生成了一个优化的块分配方案，该方案将所有相关和独立的多节点故障场景的总系统修复成本降至最低； ii。我们解决了具有新到达的块并将这些块分配给现有节点而不对原始节点上的块分布进行任何修改的实际情况； iii。我们考虑新来的节点并生成更新的优化块分布； iv。我们考虑使用可变的分数重复码优化具有不同优先级的块的存储和恢复。使用关联矩阵对这四个问题进行建模，并通过启发式求解。我们在几种情况下为我们提出的算法提供了一系列结果，以评估解决方案方法的有效性，这些方法被证明可以产生接近最佳的结果。 （C）2017由Elsevier B.V.发布

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