Combining Compression, Encryption and Fault-tolerant Coding for Distributed Storage

Storing data in distributed systems aims to offer higher bandwidth and scalability than storing locally. But, a couple of disadvantageous issues must be taken into account such as unreliability caused by faults, temporal downtimes and malicious attacks. To improve dependability, redundancy codes like parity can be used as well as more sophisticated codes such as Reed/Solomon. Another issue - security requirements - arise when data is kept in untrusted units in a network. To encrypt data, it is common to use security algorithms like AES. For efficient transfer and storage, the amount of data can be reduced by compression algorithms. All. these techniques - data distribution, fault-tolerant coding, encryption and compression - can be employed together using independent algorithms, but in a proper combination. A superposition of these techniques exploiting synergies is still an issue for research. Thus, in this paper we study proper technique combinations applied to distributed storage. The combinations are classified and examined with respect to their potential benefit and limitations. For our model, performance parameters from the distributed storage system NetRAID are used.