mlsanityData to 14 Oct 2026

A Survey on Collaborative DNN Inference for Edge Intelligence

arXiv 2207.07812 ↗First posted 16 Jul 2022cs.DC cs.LGcited by 24

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Abstract (arXiv)

With the vigorous development of artificial intelligence (AI), the intelligent applications based on deep neural network (DNN) change people's lifestyles and the production efficiency. However, the huge amount of computation and data generated from the network edge becomes the major bottleneck, and traditional cloud-based computing mode has been unable to meet the requirements of real-time processing tasks. To solve the above problems, by embedding AI model training and inference capabilities into the network edge, edge intelligence (EI) becomes a cutting-edge direction in the field of AI. Furthermore, collaborative DNN inference among the cloud, edge, and end device provides a promising way to boost the EI. Nevertheless, at present, EI oriented collaborative DNN inference is still in its early stage, lacking a systematic classification and discussion of existing research efforts. Thus motivated, we have made a comprehensive investigation on the recent studies about EI oriented collaborative DNN inference. In this paper, we firstly review the background and motivation of EI. Then, we classify four typical collaborative DNN inference paradigms for EI, and analyze the characteristics and key technologies of them. Finally, we summarize the current challenges of collaborative DNN inference, discuss the future development trend and provide the future research direction.

Key facts. Cited by 24 papers in the map (data through 14 Oct 2026). Builds on 38 of its 122 references that are in the map. First posted on arXiv 16 Jul 2022.

Builds on

38 of 122 references.

References · 38

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26 more
  1. 2020SPINN: Synergistic Progressive Inference of Neural Networks over Device and Cloudcited by 112
  2. 2021Edge Artificial Intelligence for 6G: Vision, Enabling Technologies, and Applicationscited by 97
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  7. 2018NestDNN: Resource-Aware Multi-Tenant On-Device Deep Learning for Continuous Mobile Visioncited by 68
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Cited by year (2026 to 14 Oct)

Citing papers per year: 2023: 4; 2024: 8; 2025: 8; 2026: 4.

24 papers.

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  1. 2023Green Edge AI: A Contemporary Surveycited by 25
  2. 2023EquiPocket: an E(3)-Equivariant Geometric Graph Neural Network for Ligand Binding Site Predictioncited by 15
  3. 2024Hybrid SD: Edge-Cloud Collaborative Inference for Stable Diffusion Modelscited by 11
  4. 2024Accelerating End-Cloud Collaborative Inference via Near Bubble-free Pipeline Optimizationcited by 7
  5. 2025The Larger the Merrier? Efficient Large AI Model Inference in Wireless Edge Networkscited by 7
  6. 2024Semantic Edge Computing and Semantic Communications in 6G Networks: A Unifying Survey and Research Challengescited by 5
  7. 2023Adaptive Early Exiting for Collaborative Inference over Noisy Wireless Channelscited by 3
  8. 2024Edge Graph Intelligence: Reciprocally Empowering Edge Networks with Graph Intelligencecited by 3
  9. 2024Edge-device Collaborative Computing for Multi-view Classificationcited by 2
  10. 2025Privacy-Aware Joint DNN Model Deployment and Partitioning Optimization for Collaborative Edge Inference Servicescited by 2
  11. 2025TPU-Gen: LLM-Driven Custom Tensor Processing Unit Generatorcited by 2
  12. 2025CoFormer: Collaborating with Heterogeneous Edge Devices for Scalable Transformer Inferencecited by 1
12 more
  1. 2025RockNet: Distributed Learning on Ultra-Low-Power Devicescited by 1
  2. 2026Quantization-Aware Collaborative Inference for Large Embodied AI Modelscited by 1
  3. 2026Cloud-Edge Collaborative Large Models for Robust Photovoltaic Power Forecastingcited by 1
  4. 2023High Efficiency Inference Accelerating Algorithm for NOMA-based Mobile Edge Computingcited by 0
  5. 2024Federated Learning for Collaborative Inference Systems: The Case of Early Exit Networkscited by 0
  6. 2024Distributed Convolutional Neural Network Training on Mobile and Edge Clusterscited by 0
  7. 2024A QoE-Aware Split Inference Accelerating Algorithm for NOMA-based Edge Intelligencecited by 0
  8. 2025Collaborative Inference Acceleration with Non-Penetrative Tensor Partitioningcited by 0
  9. 2025FedChip: Federated LLM for Artificial Intelligence Accelerator Chip Designcited by 0
  10. 2025GCoDE: Efficient Device-Edge Co-Inference for GNNs via Architecture-Mapping Co-Searchcited by 0
  11. 2026Safe Multi-Agent Deep Reinforcement Learning for Privacy-Aware Edge-Device Collaborative DNN Inferencecited by 0
  12. 2026GHR-VLM: Making Zero-Shot Transit Video Analytics Realizable with Grounded Hybrid Reasoningcited by 0