A Droplet Approach Based on Raptor Codes for Distributed Computing With Straggling Servers
This work addresses performance bottlenecks in distributed computing systems for applications like big data processing, though it appears incremental as it builds on existing coded computing schemes.
The paper tackles the straggler problem in distributed computing by proposing a scheme based on Raptor codes that uses droplets for intermediate computations, achieving lower computational delay compared to previous methods when decoding time is considered.
We propose a coded distributed computing scheme based on Raptor codes to address the straggler problem. In particular, we consider a scheme where each server computes intermediate values, referred to as droplets, that are either stored locally or sent over the network. Once enough droplets are collected, the computation can be completed. Compared to previous schemes in the literature, our proposed scheme achieves lower computational delay when the decoding time is taken into account.