Fault Tolerance in Distributed Systems Using Fused Data Structures

Replication is the prevalent solution to tolerate faults in large data structures hosted on distributed servers. To tolerate f crash faults (dead/unresponsive data structures) among n distinct data structures, replication requires f + 1 replicas of each data structure, resulting in nf additional backups. We present a solution, referred to as fusion that uses a combination of erasure codes and selective replication to tolerate f crash faults using just f additional fused backups. We show that our solution achieves O(n) savings in space over replication. Further, we present a solution to tolerate f Byzantine faults (malicious data structures), that requires only nf + f backups as compared to the 2nf backups required by replication. We explore the theory of fused backups and provide a library of such backups for all the data structures in the Java Collection Framework. The theoretical and experimental evaluation confirms that the fused backups are space-efficient as compared to replication, while they cause very little overhead for normal operation. To illustrate the practical usefulness of fusion, we use fused backups for reliability in Amazon´s highly available key-value store, Dynamo. While the current replication-based solution uses 300 backup structures, we present a solution that only requires 120 backup structures. This results in savings in space as well as other resources such as power.