Co-Inference Over Wireless Multi - Hop Networks

This paper focuses on the multi-splitting of DNN over wireless multi-hop networks to distribute the computing over multiple network nodes for achieving efficient edge infer-ence. The challenge is how to choose an inference routing in which both the transmission and inference can be efficiently relayed hop-by-hop. We propose a DNN multi-splitting method along with dynamical early-exit of inference based on communication and computation conditions. We formulate and then solve an optimization problem of joint routing, split points selection, and model deployment to minimize the end - to-end inference latency. The experimental results demonstrate the superiority of our work in reducing inference latency.