Merged-r Luby Transform Coded Computation for Non-Linear Tasks in Wireless Networks

Coded computation has garnered considerable attention for its ability to eliminate the stragglers' effect. Most existing works of coded computation are designed for linear tasks. They cannot handle the nonlinear tasks directly, leading to high computation, transmission and decoding latency. In this paper, considering a nonlinear task in wireless networks, we propose an efficient merged-r Luby transform (LT) coded computation scheme. First, we give the merged-r LT coding strategy to reduce the computation and transmission costs. Then, the maximum degree decoding (MDD) strategy is proposed to speed up the decoding process. Finally, we analyze and optimize the latency performance for the whole network by designing the merging parameter. Theoretical analysis and simulation results show that our proposed scheme has significant advantages over the existing ones for nonlinear tasks.