Scalable Error Isolation for Distributed Systems

In distributed systems, data corruption on a single node can propagate to other nodes in the system and cause severe outages. The probability of data corruption is already non-negligible today in large computer populations (e.g., in large datacenters). The resilience of processors is expected to decline in the near future, making it necessary to devise cost-effective software approaches to deal with data corruption. In this paper, we present SEI, an algorithm that tolerates Arbitrary State Corruption (ASC) faults and prevents data corruption from propagating across a distributed system. SEI scales in three dimensions: memory, number of processing threads, and development effort. To evaluate development effort, fault coverage, and performance with our library, we hardened two real-world applications: a DNS resolver and memcached. Hardening these applications required minimal changes to the existing code base, and the performance overhead is negligible in the case of applications that are not CPU-intensive, such as memcached. The memory overhead is negligible independent of the application when using ECC memory. Finally, SEI covers faults effectively: it detected all hardware-injected errors and reduced undetected errors from 44% down to only 0.15% of the software-injected computation errors in our experiments.