IET Communications (Dec 2021)

Global repair bandwidth cost optimization of generalized regenerating codes in clustered distributed storage systems

  • Shushi Gu,
  • Fugang Wang,
  • Qinyu Zhang,
  • Tao Huang,
  • Wei Xiang

DOI
https://doi.org/10.1049/cmu2.12289
Journal volume & issue
Vol. 15, no. 19
pp. 2469 – 2481

Abstract

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Abstract In clustered distributed storage systems (CDSSs), one of the main design goals is minimizing the transmission cost during the failed storage nodes repairing. Generalized regenerating codes (GRCs) are proposed to balance the intra‐cluster repair bandwidth and the inter‐cluster repair bandwidth for guaranteeing data availability. The trade‐off performance of GRCs illustrates that, it can reduce storage overhead and inter‐cluster repair bandwidths simultaneously. However, in practical big data storage scenarios, GRCs cannot give an effective solution to handle the heterogeneity of bandwidth costs among different clusters for node failures recovery. This paper proposes an asymmetric bandwidth allocation strategy (ABAS) of GRCs for the inter‐cluster repair in heterogeneous CDSSs. Furthermore, an upper bound of the achievable capacity of ABAS is derived based on the information flow graph (IFG), and the constraints of storage capacity and intra‐cluster repair bandwidth are also elaborated. Then, a metric termed global repair bandwidth cost (GRBC), which can be minimized regarding of the inter‐cluster repair bandwidths by solving a linear programming problem, is defined. The numerical results demonstrate that, maintaining the same data availability and storage overhead, the proposed ABAS of GRCs can effectively reduce the GRBC compared to the traditional symmetric bandwidth allocation schemes.

Keywords