Network Coding for Distributed Storage Systems

Abstract

Distributed storage systems provide reliable access to data through redundancy spread over individually unreliable nodes. Application scenarios include data centers, peer-to-peer storage systems, and storage in wireless networks. Storing data using an erasure code, in fragments spread across nodes, requires less redundancy than simple replication for the same level of reliability. However, since fragments must be periodically replaced as nodes fail, a key question is how to generate encoded fragments in a distributed way while transferring as little data as possible across the network.For an erasure coded system, a common practice to repair from a node failure is for a new node to download subsets of data stored at a number of surviving nodes, reconstruct a lost coded block using the downloaded data, and store it at the new node. We show that this procedure is sub-optimal. We introduce the notion of regenerating codes, which allow a new node to download functions of the stored data from the surviving nodes. We show that regenerating codes can significantly reduce the repair bandwidth. Further, we show that there is a fundamental tradeoff between storage and repair bandwidth which we theoretically characterize using flow arguments on an appropriately constructed graph. By invoking constructive results in network coding, we introduce regenerating codes that can achieve any point in this optimal tradeoff.

Locally Repairable Fractional Repetition Codes

“…재생 부호에 서는 복구 대역폭과 한 노드의 저장용량 사이에 트레 이드오프가 존재함이 잘 알려져 있다 [7] . 이 트레이드 오프 곡선의 양 끝단에 해당하는 부호를 각각 최소 저 장공간 재생부호(minimum storage regenerating code; MSR code)와 최소 대역폭 재생부호(minimum repair-bandwidth regenerating code; MBR code)라고…”

An update model for network coding in cloud storage systems

“…Recently, there are many efforts in practical network coding for storage systems [22], [23], [24]. However, there has been no work addressing the update problem defined in Sec.…”

“…To this end, different symmetric and asymmetric network and erasure coding mechanisms have been proposed [26], [22], [27] that either rebuild a node with the same functionality as the failed node (functional repair) from the surviving nodes [22], [27], or reconstruct an exact copy of the failed node (exact repair) [28]. In [22], the notion of regenerating codes has been introduced to decrease the repair bandwidth by allowing a new node to communicate functions of the stored data from the surviving nodes. Similarly, in [27], another solution for multiple node failures in a distributed storage system has been proposed.…”

Performance evaluation of a peer-to-peer backup system using buffering at the edge

“…Our proposal differs from existing approaches [4,5,8,9,10,11,12,13] by taking into account the low-level structure of the network. Indeed, most peer-to-peer applications ignore the presence of a gateway in between each peer and the Internet.…”