Smart Redundancy for Distributed Computation

Many distributed software systems allow participation by large numbers of untrusted, potentially faulty components on an open network. As faults are inevitable in this setting, these systems utilize redundancy and replication to achieve fault tolerance. In this paper, we present a novel "smart" redundancy technique called iterative redundancy, which ensures efficient replication of computation and data given finite processing and storage resources, even when facing Byzantine faults. Iterative redundancy is more efficient and more adaptive than comparable state-of-the-art techniques that operate in environments with unknown system resource reliability. We show how systems that solve computational problems using a network of independent nodes can benefit from iterative redundancy. We present a formal analytical analysis and an empirical analysis, demonstrate iterative redundancy on a real-world volunteer-computing system, and compare it to existing methods.