318 research outputs found
Explicit Construction of Minimum Bandwidth Rack-Aware Regenerating Codes
In large data centers, storage nodes are organized in racks, and the
cross-rack communication dominates the system bandwidth. We explicitly
construct codes for exact repair of single node failures that achieve the
optimal tradeoff between the storage redundancy and cross-rack repair bandwidth
at the minimum bandwidth point (i.e., the cross-rack bandwidth equals the
storage size per node). Moreover, we explore the node repair when only a few
number of helper racks are connected. Thus we provide explicit constructions of
codes for rack-aware storage with the minimum cross-rack repair bandwidth,
lowest possible redundancy, and small repair degree (i.e., the number of helper
racks connected for repair).Comment: 4 pages, 1 figure. arXiv admin note: text overlap with
arXiv:2101.0873
A Class of MSR Codes for Clustered Distributed Storage
Clustered distributed storage models real data centers where intra- and
cross-cluster repair bandwidths are different. In this paper, exact-repair
minimum-storage-regenerating (MSR) codes achieving capacity of clustered
distributed storage are designed. Focus is given on two cases: and
, where is the ratio of the available cross- and
intra-cluster repair bandwidths, is the total number of distributed nodes
and is the number of contact nodes in data retrieval. The former represents
the scenario where cross-cluster communication is not allowed, while the latter
corresponds to the case of minimum cross-cluster bandwidth that is possible
under the minimum storage overhead constraint. For the case, two
types of locally repairable codes are proven to achieve the MSR point. As for
, an explicit MSR coding scheme is suggested for the
two-cluster situation under the specific condition of .Comment: 9 pages, a part of this paper is submitted to IEEE ISIT201
Global repair bandwidth cost optimization of generalized regenerating codes in clustered distributed storage systems
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
TOWARDS DIGITAL TWINS FOR OPTIMIZING METRICS IN DISTRIBUTED STORAGE SYSTEMS - A REVIEW
With the exponential data growth, there is a crucial need for highly available, scalable, reliable, and cost-effective Distributed Storage Systems (DSSs). To ensure such efficient and fault tolerant systems, replication and erasure coding techniques are typically used in traditional DSSs. However, these systems are prone to failure and require different failure prevention and recovery algorithms. Failure recovery of DSS and data reconstruction techniques take into consideration different performance metrics optimization in the recovery process. In this paper, DSS performance metrics are introduced. Several recent papers related to adopting erasure coding in DSSs are surveyed together with highlighting related performance metrics introduced in the context of these papers. Next, we present recent literature where Digital Twins (DTs) are involved in monitoring DSSs and assisting the data center managers in intelligent decision-making. Finally, important open issues are identified to inspire future studies for fully efficient DSSs
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