Lagrange Coded Computing with Sparsity Constraints

Abstract

In this paper, we propose a distributed coding scheme that allows for lower computation cost per computing node than the standard Lagrange Coded Computing scheme. The proposed coding scheme is useful for cases where the elements of the input data set are of large dimensions and the computing nodes have limited computation power. This coding scheme provides a trade-off between the computation cost per worker and the recovery threshold in a distributed coded computing framework. The proposed scheme is also extended to provide data privacy against at most t colluding worker nodes in the system.