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6. 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.