When locally repairable codes meet regenerating codes &amp;#x2014; What if some helpers are unavailable

Ahmad, Imad; Wang, Chih-Chun

doi:10.1109/isit.2015.7282575

Cited by 5 publications

(31 citation statements)

References 12 publications

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“…As a result, at least when considering only single node failure, there is no clear advantage of DHS over SHS. However, for the multiple failures scenario, we have shown in a separate work [2] that it is possible to have DHS≻SHS=BHS. Specifically, under some scenarios, only DHS can strictly outperform BHS while the best SHS design is no better than the simple BHS solution.…”

Section: B Dynamic Versus Stationary Helper Selection Schemesmentioning

confidence: 90%

“…For example, when (n, k, d) = (5, 3, 2), one can prove that min all codes α MSR = M 2 based on the definition in (8). We thus say that the MSR point of the best possible scheme is α * MSR = M 2 for (n, k, d) = (5,3,2). In contrast, the alternative MSR definition will say that the MSR point does not exist for the parameter (n, k, d) = (5, 3, 2) since no scheme can achieve…”

Section: Optimality and Weak Optimality Of A Helper Selection Schemementioning

confidence: 99%

“…By our construction x (1) , as an existing active node, is repaired before the newcomer y (1) and there is an edge (x (1) out , y (1) in ) in G (1) . Starting now from G (1) , we choose another w (2) which is not one of x (1) and y (1) and let this node fail. Such w (2) always exists since n is odd by condition (i).…”

Section: The Conversementioning

confidence: 99%

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When and by how much can helper node selection improve regenerating codes?

Ahmad¹,

Wang²

2014

2014 52nd Annual Allerton Conference on Communication, Control, and Computing (Allerton)

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Abstract-Regenerating codes (RCs) can significantly reduce the repair-bandwidth of distributed storage networks. Initially, the analysis of RCs was based on the assumption that during the repair process, the newcomer does not distinguish (among all surviving nodes) which nodes to access, i.e., the newcomer is oblivious to the set of helpers being used. Such a scheme is termed the blind repair (BR) scheme. Nonetheless, it is intuitive in practice that the newcomer should choose to access only those "good" helpers. In this paper, a new characterization of the effect of choosing the helper nodes in terms of the storagebandwidth tradeoff is given. Specifically, answers to the following fundamental questions are given: Under what conditions does proactively choosing the helper nodes improve the storagebandwidth tradeoff? Can this improvement be analytically quantified?This paper answers the former question by providing a necessary and sufficient condition under which optimally choosing good helpers strictly improves the storage-bandwidth tradeoff. To answer the latter question, a low-complexity helper selection solution, termed the family repair (FR) scheme, is proposed and the corresponding storage/repair-bandwidth curve is characterized. For example, consider a distributed storage network with 60 total number of nodes and the network is resilient against 50 node failures. If the number of helper nodes is 10, then the FR scheme and its variant demonstrate 27% reduction in the repair-bandwidth when compared to the BR solution. This paper also proves that under some design parameters, the FR scheme is indeed optimal among all helper selection schemes. An explicit construction of an exact-repair code is also proposed that can achieve the minimum-bandwidth-regenerating point of the FR scheme. The new exact-repair code can be viewed as a generalization of the existing fractional repetition code.

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Section: B Dynamic Versus Stationary Helper Selection Schemesmentioning

confidence: 90%

Section: Optimality and Weak Optimality Of A Helper Selection Schemementioning

confidence: 99%

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When and by how much can helper node selection improve regenerating codes?

Ahmad¹,

Wang²

2014

2014 52nd Annual Allerton Conference on Communication, Control, and Computing (Allerton)

Self Cite

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“…In [11], Kamath et al gave an existential proof without presenting an explicit construction. Another direction of combining RCs and LRCs is to use repair locality for selecting the accessed nodes in a RC [29], while an interpretation of LRCs as exact RCs was presented in [30]. Two different erasure codes, product and LRC codes, are used to dynamically adapt to the workload changes in Hadoop Adaptively-Coded Distributed File System (HACFS) [31].…”

Section: Related Workmentioning

confidence: 99%

Network traffic driven storage repair

Gligoroski

Kralevska

Jensen

et al. 2019

IJBDI

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Recently we constructed an explicit family of locally repairable and locally regenerating codes. Their existence was proven by Kamath et al. but no explicit construction was given. Our design is based on HashTag codes that can have different sub-packetization levels. In this work we emphasize the importance of having two ways to repair a node: repair only with local parity nodes or repair with both local and global parity nodes. We say that the repair strategy is network traffic driven since it is in connection with the concrete system and code parameters: the repair bandwidth of the code, the number of I/O operations, the access time for the contacted parts and the size of the stored file. We show the benefits of having repair duality in one practical example implemented in Hadoop. We also give algorithms for efficient repair of the global parity nodes.

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“…In [12], Kamath et al gave an existential proof without presenting an explicit construction. Another direction of combining RCs and LRCs is to use repair locality for selecting the accessed nodes in a RC [13], while an interpretation of LRCs as exact RCs was presented in [14]. Two different erasure codes, product and LRC codes, are used to optimize for recovery performance and reduce the storage overhead in [15].…”

Section: Introductionmentioning

confidence: 99%

Repair Duality with Locally Repairable and Locally Regenerating Codes

Gligoroski¹,

Kralevska²,

Jensen³

et al. 2017

2017 IEEE 15th Intl Conf on Dependable, Autonomic and Secure Computing, 15th Intl Conf on Pervasive Intelligence and Computing,

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We construct an explicit family of locally repairable and locally regenerating codes whose existence was proven in a recent work by Kamath et al. about codes with local regeneration but no explicit construction was given. This explicit family of codes is based on HashTag codes. HashTag codes are recently defined vector codes with different vector length α (also called a sub-packetization level) that achieve the optimal repair bandwidth of MSR codes or near-optimal repair bandwidth depending on the sub-packetization level. We applied the technique of paritysplitting code construction. We show that the lower bound on the size of the finite field for the presented explicit code constructions can be lower than the one given in the work of Kamath et al. Finally, we discuss the importance of having two ways for node repair with locally regenerating HashTag codes: repair only with local parity nodes or repair with both local and global parity nodes. To the best of the authors' knowledge, this is the first work where this duality in repair process is discussed. We give a practical example and experimental results in Hadoop where we show the benefits of having this repair duality.

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When locally repairable codes meet regenerating codes — What if some helpers are unavailable

Cited by 5 publications

References 12 publications

When and by how much can helper node selection improve regenerating codes?

When and by how much can helper node selection improve regenerating codes?

Network traffic driven storage repair

Repair Duality with Locally Repairable and Locally Regenerating Codes

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