Design, implementation, and deployment of multi-task neural networks in programmable data-planes

Journal article

The increasing demand for real-time inference on high-volume network traffic has led to the rise of in-network machine learning, where programmable switches execute various models directly in the data-plane at line rate. Effective network management often involves multiple prediction tasks, such as predicting bit rate, flow size, or traffic class; however, existing solutions deploy separate models for each task, placing a significant burden on the data-plane and leading to substantial resource consumption when deploying multiple tasks. To address this limitation, we introduce MUTA, a novel in-network multi-task learning framework that enables concurrent inference of multiple tasks in the data-plane, without exhausting available resources. MUTA builds a multi-task neural network to share feature representations across tasks and introduces a data-plane mapping methodology to fit it within network switches. Additionally, MUTA enhances scalability by supporting distributed deployment, where different layers of a multi-task model can be offloaded across multiple switches. An orchestrator employs multi-objective optimization to determine optimal model placement in multi-path networks. MUTA is deployed on P4 hardware switches, and is shown to reduce memory requirements by x10.5, while at the same time improving accuracy by up to 9.14% using limited training data, compared with state-of-the-art single-task learning solutions.

Authors: Zhang, K; Zheng, C; Samaan, N; Karmouch, A; Zilberman, N

• Publication status: Published
• Peer review status: Peer reviewed
• Publisher: IEEE
• Journal: IEEE Transactions on Network and Service Management
• Volume: 23
• Pages: 740-755
• Publication date: 2025-11-06
• Acceptance date: 2025-10-30
• DOI: 10.1109/TNSM.2025.3629642
• EISSN: 2373-7379
• ISSN: 1932-4537
• Language: English
• Keywords: in-network computing; P4; multi-task learning; neural networks; programmable data-planes