Collaborative Deep Neural Network Inference

Collaborative deep neural network (DNN) inference aims to distribute the computationally intensive task of DNN processing across multiple devices, such as edge servers and IoT devices, to improve efficiency and reduce latency. Current research focuses on optimizing this distribution using reinforcement learning algorithms to manage resource allocation, task offloading, and sampling rates while guaranteeing accuracy and addressing privacy concerns through techniques like data partitioning. This approach is crucial for enabling real-time AI applications in resource-constrained environments and has significant implications for various fields, including industrial IoT and edge intelligence.