Performance Analysis on Distributed Storage Systems in Ring Networks

Abstract

Distributed storage systems can provide reliable service of data storage. Lots of scenarios, such as data center, P2P network are all applications of distributed storage systems. There are mainly three storage schemes for distributed storage systems, including replication , erasure codes and regenerating codes [2] . With the same storage space, more reliable data storage is assured by erasure codes than replication . However, replication can save more repair bandwidth (i.e., the communication cost for node repair) than erasure codes . To ensure both high reliability and low repair bandwidth, regenerating codes are intensively investigated. In practical systems, the communication between two nodes may be restricted by physical factors or economic considerations, such as transmission distance or network traffic. In this paper, we propose a novel model considering the connectivity limitations in ring networks. Each node can only connect to or communicate with its neighbors within a given range. Inspired by the concept of regenerating codes , we investigate the theoretical necessary condition for all possible storage codes. Then, a tradeoff between storage space and repair bandwidth is derived by analyzing the information flow graph of our model. Two interesting points on the tradeoff curve are further investigated, corresponding to the ring minimum-storage-regenerating (rMSR) codes, and the ring minimum-bandwidth-regenerating (rMBR) codes. Besides, two types of code constructions are presented. (i) For both rMSR and rMBR codes, we provide code constructions under exact repair models. (ii) Under functional repair models, we derive the size of the coding finite field, based on which the algorithm in [3] can be applied to construct the corresponding codes. And finally, the superiority of our codes is validated by both theoretical and simulation results. Simulations show that our codes outperform baseline schemes, and the reduction on repair bandwidth can be up to 66% of the original data size.