On low repair complexity storage codes via group divisible designs

Zhu, Bing; Shum, Kenneth W.; Li, Hui; Li, Shuo-Yen Robert

doi:10.1109/iscc.2014.6912604

Cited by 14 publications

(11 citation statements)

References 19 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The concept of an FR code is introduced in the pioneer work [10], wherein the authors also proposed explicit code constructions from regular graphs and Steiner systems. Several recent studies extend the construction of FR codes to a larger set of parameters, which are mainly based on the graph theory (e.g., bipartite cage graph [11] and extremal graph [12], [13]) and combinatorial designs (e.g., transversal designs [12], resolvable designs [14], group divisible designs [15], Hadamard designs [16], perfect difference families [17], relative difference sets [18] and partially ordered sets [19]). Further, Pawar et al [20] proposed a randomized scheme for constructing FR codes, which is based on the balls-and-bins model.…”

Section: A Related Workmentioning

confidence: 99%

See 1 more Smart Citation

On the Duality and File Size Hierarchy of Fractional Repetition Codes

Zhu

Shum

2018

The Computer Journal

Self Cite

View full text Add to dashboard Cite

Distributed storage systems that deploy erasure codes can provide better features such as lower storage overhead and higher data reliability. In this paper, we focus on fractional repetition (FR) codes, which are a class of storage codes characterized by the features of uncoded exact repair and minimum repair bandwidth. We study the duality of FR codes, and investigate the relationship between the supported file size of an FR code and its dual code. Based on the established relationship, we derive an improved dual bound on the supported file size of FR codes. We further show that FR codes constructed from t-designs are optimal when the size of the stored file is sufficiently large. Moreover, we present the tensor product technique for combining FR codes, and elaborate on the file size hierarchy of resulting codes.

show abstract

Section: A Related Workmentioning

confidence: 99%

“…which completes the proof. We refer to the inequality in (15) as the dual bound on the supported file size. Then, the dual bound in (15) gives This bound can be achieved by the (9, 2, 6, 3)-FR code listed in the database [21] with the following incidence matrix: …”

Section: B An Improved Dual Boundmentioning

confidence: 99%

On the Duality and File Size Hierarchy of Fractional Repetition Codes

Zhu

Shum

2018

The Computer Journal

Self Cite

View full text Add to dashboard Cite

show abstract

“…Each subfile is stored in K node, and the size of coded packet is / B fK . codes have advantages in storage overhead, followed by the LRC based on (6,4,12,2) FR code. The storage overhead of SRC is the larges t(see Figure 5).…”

Section: Storage Overheadmentioning

confidence: 99%

Locally Repairable Codes Based on Fractional Repetition Codes in Distributed Storage Systems

Wang¹,

Wang²,

Li³

et al. 2018

dtcse

View full text Add to dashboard Cite

In order to improve the reliability of distributed storage systems (DSS) and repair efficiency of failed nodes, a new coding scheme, termed as locally repairable codes (LRC) based on fractional repetition (FR) codes, is proposed in this paper. Specifically, the proposed LRC based on FR codes divide the nodes into multiple local groups, and the FR codes with repetition degree 2   are adopted in each local group. The LRC based on FR codes can achieve the exact repair for single failed node in the local group, and rapid repair for multiple failed nodes in DSS with lower repair locality. Furthermore, compared with Reed-Solomon (RS) codes and simple regenerating codes (SRC), the LRC based on FR codes have remarkable advantages in repair bandwidth overhead.

show abstract

“…In this case, we can adopt a [9,7] MDS code as the outer code such that the seven source symbols can be decoded from any three storage nodes. When a storage node fails, the lost symbols can be recovered by downloading the corresponding replicas from other surviving nodes.…”

Section: Flexible Fractional Repetition Codesmentioning

confidence: 99%

Heterogeneity-Aware Codes With Uncoded Repair for Distributed Storage Systems

Zhu

Shum

2015

IEEE Commun. Lett.

Self Cite

View full text Add to dashboard Cite

In practical large-scale distributed storage systems, node failures are unavoidable. It is therefore desirable to quickly recreate the failed nodes in order to maintain the system integrity. In this letter, we consider a family of erasure codes that provide uncoded repair, where the failed node is regenerated by transfer of data without extra arithmetic operations. We introduce flexible fractional repetition (FFR) code, of which the coding scheme is a concatenation of an outer MDS code and an inner repetition code. Our proposed codes are applicable to the heterogeneous network environment where node storage capacities and packet repetition degrees vary in a wide range. We present explicit constructions of FFR codes by utilizing combinatorial designs. We further propose a heuristic code construction. Evaluation results show that FFR codes outperform regenerating codes in node repair efficiency.

show abstract

On low repair complexity storage codes via group divisible designs

Cited by 14 publications

References 19 publications

On the Duality and File Size Hierarchy of Fractional Repetition Codes

On the Duality and File Size Hierarchy of Fractional Repetition Codes

Locally Repairable Codes Based on Fractional Repetition Codes in Distributed Storage Systems

Heterogeneity-Aware Codes With Uncoded Repair for Distributed Storage Systems

Contact Info

Product

Resources

About