Concurrent Regenerating Codes and Scalable Application in Network Storage

TL;DR

This paper introduces concurrent regenerating codes for network storage, providing a unified framework for efficient repair and scalable redundancy management, with analytical tradeoffs and practical construction methods.

Contribution

It unifies concurrent regenerating codes with existing models, analyzes their properties, and explores their application in scalable storage systems.

Findings

Derived a general storage-bandwidth tradeoff curve.

Provided closed-form expressions for key points on the tradeoff curve.

Demonstrated construction methods from existing regenerating codes.

Abstract

To recover simultaneous multiple failures in erasure coded storage systems, Patrick Lee et al introduce concurrent repair based minimal storage regenerating codes to reduce repair traffic. The architecture of this approach is simpler and more practical than that of the cooperative mechanism in non-fully distributed environment, hence this paper unifies such class of regenerating codes as concurrent regenerating codes and further studies its characteristics by analyzing cut-based information flow graph in the multiple-node recovery model. We present a general storage-bandwidth tradeoff and give closed-form expressions for the points on the curve, including concurrent repair mechanism based on minimal bandwidth regenerating codes. We show that the general concurrent regenerating codes can be constructed by reforming the existing single-node regenerating codes or multiplenode cooperative regenerating codes. Moreover, a connection to strong-MDS is also analyzed. On the other respect, the application of RGC is hardly limited to "repairing". It is of great significance for "scaling", a scenario where we need to increase(decrease) nodes to upgrade(degrade) redundancy and reliability. Thus, by clarifying the similarities and differences, we integrate them into a unified model to adjust to the dynamic storage network.