List-Decodable Coded Computing: Breaking the Adversarial Toleration Barrier
This work addresses the challenge of tolerating more adversaries in distributed computing systems, representing a significant but incremental advance in coded computing.
The paper tackles the problem of coded computing in the presence of adversarial workers by proposing techniques to break the adversarial toleration threshold barrier, showing that folded Lagrange coded computing (FLCC) improves the threshold by a factor of two asymptotically compared to LCC.
We consider the problem of coded computing, where a computational task is performed in a distributed fashion in the presence of adversarial workers. We propose techniques to break the adversarial toleration threshold barrier previously known in coded computing. More specifically, we leverage list-decoding techniques for folded Reed-Solomon codes and propose novel algorithms to recover the correct codeword using side information. In the coded computing setting, we show how the master node can perform certain carefully designed extra computations to obtain the side information. The workload of computing this side information is negligible compared to the computations done by each worker. This side information is then utilized to prune the output of the list decoder and uniquely recover the true outcome. We further propose folded Lagrange coded computing (FLCC) to incorporate the developed techniques into a specific coded computing setting. Our results show that FLCC outperforms LCC by breaking the barrier on the number of adversaries that can be tolerated. In particular, the corresponding threshold in FLCC is improved by a factor of two asymptotically compared to that of LCC.