Cost-Bandwidth Tradeoff In Distributed Storage Systems

TL;DR

This paper investigates the theoretical relationship between storage cost and repair bandwidth in distributed storage systems, demonstrating that generalized regenerating codes can achieve any point on this tradeoff curve.

Contribution

It introduces the concept of generalized regenerating codes, extending previous regeneration codes to optimize the cost-bandwidth tradeoff in distributed storage.

Findings

Any point on the cost-bandwidth tradeoff curve can be achieved.

Generalized regenerating codes outperform traditional regeneration codes.

Theoretical framework for cost-efficient data regeneration in distributed systems.

Abstract

Distributed storage systems are mainly justified due to the limited amount of storage capacity and improving the reliability through distributing data over multiple storage nodes. On the other hand, it may happen the data is stored in unreliable nodes, while it is desired the end user to have a reliable access to the stored data. So, in an event that a node is damaged, to prevent the system reliability to regress, it is necessary to regenerate a new node with the same amount of stored data as the damaged node to retain the number of storage nodes, thereby having the previous reliability. This requires the new node to connect to some of existing nodes and downloads the required information, thereby occupying some bandwidth, called the repair bandwidth. On the other hand, it is more likely the cost of downloading varies across different nodes. This paper aims at investigating the theoretical cost-bandwidth tradeoff, and more importantly, it is demonstrated that any point on this curve can be achieved through the use of the so called generalized regenerating codes which is an enhancement of the regeneration codes introduced by Dimakis et al. in [1].