Towards self-repairing replication-based storage systems using untrusted clouds

Distributed storage systems store data redundantly at multiple servers which are geographically spread through- out the world. This basic approach would be sufficient in handling server failure due to natural faults, because when one server fails, data from healthy servers can be used to restore the desired redundancy level. However, in a set- ting where servers are untrusted and can behave maliciously, data redundancy must be used in tandem with Remote Data Checking (RDC) to ensure that the redundancy level of the storage systems is maintained over time. All previous RDC schemes for distributed systems impose a heavy burden on the data owner (client) during data maintenance: To repair data at a faulty server, the data owner needs to first download a large amount of data, re-generate the data to be stored at a new server, and then upload this data at a new healthy server. We propose RDC - SR, a novel RDC scheme for replication-based distributed storage systems. RDC - SR enables Server-side Repair (thus taking advantage of the premium connections available between a CSP's data centers) and places a minimal load on the data owner who only has to act as a repair coordinator. The main insight behind RDC - SR is that the replicas are differentiated based on a controllable amount of masking, which offers RDC - SR flexibility in handling different adversarial strengths. Also, replica generation must be time consuming in order to avoid certain colluding attacks from malicious servers. Our prototype for RDC - SR built on Amazon AWS validates the practicality of this new approach.