Heterogeneous Coded Distributed Computing with Nonuniform Input File Popularity

This paper studies the heterogeneous coded distributed computing (CDC) where input files required for job access have nonuniform popularity. We propose a file placement strategy that can handle an arbitrary number of input files and a nested coded shuffling strategy to effectively explore coded multicasting opportunities. We then formulate the joint optimization of the proposed file placement strategy and shuffling design variables into a mixed-integer linear programming (MILP) problem. To reduce the computational complexity, we propose a simple two-file-group-based approach to obtain an approximate solution. Numerical results show that the proposed two-file-group-based approach achieves nearly the same performance as solving the MILP problem using the conventional branch-and-cut method but with substantially lower computational complexity.