Joint Optimization of Offloading, Batching and DVFS for Multiuser Co-Inference

Understand

With the growing integration of artificial intelligence in mobile applications, a substantial number of deep neural network (DNN) inference requests are generated daily by mobile devices.

• Serving these requests presents significant challenges due to limited device resources and strict latency requirements.
• Therefore, edge-device co-inference has emerged as an effective paradigm to address these issues.
• In this study, we focus on a scenario where multiple mobile devices offload inference tasks to an edge server equipped with a graphics processing unit (GPU).