In-network redundancy generation for opportunistic speedup of data backup

Erasure coding is a storage-efficient alternative to replication for achieving reliable data backup in distributed storage systems. During the storage process, traditional erasure codes require a unique source node to create and upload all the redundant data to the different storage nodes. However, such a source node may have limited communication and computation capabilities, which constrain the storage process throughput. Moreover, the source node and the different storage nodes might not be able to send and receive data simultaneously – e.g., nodes might be busy in a datacenter setting, or simply be offline in a peer-to-peer setting – which can further threaten the efficacy of the overall storage process. In this paper we propose an “in-network” redundancy generation process that leverages on the self-repairing property of the novel SRC codes. This in-network redundancy generation allows storage nodes to generate new redundant data by exchanging partial information among themselves, improving the throughput of the storage process. The process is carried out asynchronously, utilizing spare bandwidth and computing resources from the storage nodes. We analytically show that the performance of this technique relies on an efficient usage of the spare node resources, and we derive a set of scheduling algorithms to maximize the same. We experimentally show that our algorithms can, depending on the environment characteristics, increase the throughput of the storage process significantly with respect to the classical naive storage approach. Keywords-distributed storage; erasure codes; backup;