A Survey on Edge Computing Systems and Tools
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Abstract (arXiv)
Driven by the visions of Internet of Things and 5G communications, the edge computing systems integrate computing, storage and network resources at the edge of the network to provide computing infrastructure, enabling developers to quickly develop and deploy edge applications. Nowadays the edge computing systems have received widespread attention in both industry and academia. To explore new research opportunities and assist users in selecting suitable edge computing systems for specific applications, this survey paper provides a comprehensive overview of the existing edge computing systems and introduces representative projects. A comparison of open source tools is presented according to their applicability. Finally, we highlight energy efficiency and deep learning optimization of edge computing systems. Open issues for analyzing and designing an edge computing system are also studied in this survey.
Key facts. Cited by 17 papers in the map (data through 14 Oct 2026). First posted on arXiv 7 Nov 2019.
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Citing papers per year: 2022: 1; 2023: 4; 2024: 5; 2025: 4; 2026: 3.
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- 2023Topology-aware Federated Learning in Edge Computing: A Comprehensive Surveycited by 23
- 2024NetTrack: Tracking Highly Dynamic Objects with a Netcited by 22
- 2023A Survey on Approximate Edge AI for Energy Efficient Autonomous Driving Servicescited by 14
- 2025Edge-Cloud Collaborative Computing on Distributed Intelligence and Model Optimization: A Surveycited by 14
- 2024Training Machine Learning models at the Edge: A Surveycited by 11
- 2023Industrial Internet of Things Intelligence Empowering Smart Manufacturing: A Literature Reviewcited by 8
- 2022Distributed intelligence on the Edge-to-Cloud Continuum: A systematic literature reviewcited by 6
- 2023EnforceSNN: Enabling Resilient and Energy-Efficient Spiking Neural Network Inference considering Approximate DRAMs for Embedded Systemscited by 6
- 2024Edge Graph Intelligence: Reciprocally Empowering Edge Networks with Graph Intelligencecited by 3
- 2025Adaptive AI Agent Placement and Migration in Edge Intelligence Systemscited by 3
- 2024Task-Oriented Real-time Visual Inference for IoVT Systems: A Co-design Framework of Neural Networks and Edge Deploymentcited by 0
- 2024Enhanced Real-Time Threat Detection in 5G Networks: A Self-Attention RNN Autoencoder Approach for Spectral Intrusion Analysiscited by 0
5 more
- 2025MECKD: Deep Learning-Based Fall Detection in Multilayer Mobile Edge Computing With Knowledge Distillationcited by 0
- 2025Rethinking Inference Placement for Deep Learning across Edge and Cloud Platforms: A Multi-Objective Optimization Perspective and Future Directionscited by 0
- 2026A Delta-Aware Orchestration Framework for Scalable Multi-Agent Edge Computingcited by 0
- 2026EdgeServing: Deadline-Aware Multi-DNN Serving at the Edgecited by 0
- 2026CST: Collaborative Selective Transmission for Communication-Efficient Multimodal Edge Inferencecited by 0
- 2026CST: Collaborative Selective Transmission for Communication-Efficient Multimodal Edge Inference22 Aug 2026
- 2026EdgeServing: Deadline-Aware Multi-DNN Serving at the Edge7 May 2026
- 2026A Delta-Aware Orchestration Framework for Scalable Multi-Agent Edge Computing22 Apr 2026
- 2025Rethinking Inference Placement for Deep Learning across Edge and Cloud Platforms: A Multi-Objective Optimization Perspective and Future Directions27 Oct 2025
- 2025MECKD: Deep Learning-Based Fall Detection in Multilayer Mobile Edge Computing With Knowledge Distillation4 Oct 2025
- 2025Adaptive AI Agent Placement and Migration in Edge Intelligence Systems5 Aug 2025
- 2025Edge-Cloud Collaborative Computing on Distributed Intelligence and Model Optimization: A Survey3 May 2025
- 2024Enhanced Real-Time Threat Detection in 5G Networks: A Self-Attention RNN Autoencoder Approach for Spectral Intrusion Analysis5 Nov 2024
- 2024Task-Oriented Real-time Visual Inference for IoVT Systems: A Co-design Framework of Neural Networks and Edge Deployment29 Oct 2024
- 2024Edge Graph Intelligence: Reciprocally Empowering Edge Networks with Graph Intelligence7 Jul 2024
- 2024NetTrack: Tracking Highly Dynamic Objects with a Net17 Mar 2024
- 2024Training Machine Learning models at the Edge: A Survey5 Mar 2024
5 more
- 2023Industrial Internet of Things Intelligence Empowering Smart Manufacturing: A Literature Review2 Dec 2023
- 2023A Survey on Approximate Edge AI for Energy Efficient Autonomous Driving Services13 Apr 2023
- 2023EnforceSNN: Enabling Resilient and Energy-Efficient Spiking Neural Network Inference considering Approximate DRAMs for Embedded Systems8 Apr 2023
- 2023Topology-aware Federated Learning in Edge Computing: A Comprehensive Survey6 Feb 2023
- 2022Distributed intelligence on the Edge-to-Cloud Continuum: A systematic literature review29 Apr 2022
- 2023Topology-aware Federated Learning in Edge Computing: A Comprehensive Surveycited by 23
- 2024NetTrack: Tracking Highly Dynamic Objects with a Netcited by 22
- 2023A Survey on Approximate Edge AI for Energy Efficient Autonomous Driving Servicescited by 14
- 2025Edge-Cloud Collaborative Computing on Distributed Intelligence and Model Optimization: A Surveycited by 14
- 2024Training Machine Learning models at the Edge: A Surveycited by 11
- 2023Industrial Internet of Things Intelligence Empowering Smart Manufacturing: A Literature Reviewcited by 8
- 2022Distributed intelligence on the Edge-to-Cloud Continuum: A systematic literature reviewcited by 6
- 2023EnforceSNN: Enabling Resilient and Energy-Efficient Spiking Neural Network Inference considering Approximate DRAMs for Embedded Systemscited by 6
- 2024Edge Graph Intelligence: Reciprocally Empowering Edge Networks with Graph Intelligencecited by 3
- 2024Task-Oriented Real-time Visual Inference for IoVT Systems: A Co-design Framework of Neural Networks and Edge Deploymentcited by 0
- 2024Enhanced Real-Time Threat Detection in 5G Networks: A Self-Attention RNN Autoencoder Approach for Spectral Intrusion Analysiscited by 0
- 2025MECKD: Deep Learning-Based Fall Detection in Multilayer Mobile Edge Computing With Knowledge Distillationcited by 0
12 most cited of 14 All 14 (JSON)
- 2026CST: Collaborative Selective Transmission for Communication-Efficient Multimodal Edge Inference22 Aug 2026
- 2026A Delta-Aware Orchestration Framework for Scalable Multi-Agent Edge Computing22 Apr 2026
- 2025MECKD: Deep Learning-Based Fall Detection in Multilayer Mobile Edge Computing With Knowledge Distillation4 Oct 2025
- 2025Edge-Cloud Collaborative Computing on Distributed Intelligence and Model Optimization: A Survey3 May 2025
- 2024Enhanced Real-Time Threat Detection in 5G Networks: A Self-Attention RNN Autoencoder Approach for Spectral Intrusion Analysis5 Nov 2024
- 2024Task-Oriented Real-time Visual Inference for IoVT Systems: A Co-design Framework of Neural Networks and Edge Deployment29 Oct 2024
- 2024Edge Graph Intelligence: Reciprocally Empowering Edge Networks with Graph Intelligence7 Jul 2024
- 2024NetTrack: Tracking Highly Dynamic Objects with a Net17 Mar 2024
- 2024Training Machine Learning models at the Edge: A Survey5 Mar 2024
- 2023Industrial Internet of Things Intelligence Empowering Smart Manufacturing: A Literature Review2 Dec 2023
- 2023A Survey on Approximate Edge AI for Energy Efficient Autonomous Driving Services13 Apr 2023
- 2023EnforceSNN: Enabling Resilient and Energy-Efficient Spiking Neural Network Inference considering Approximate DRAMs for Embedded Systems8 Apr 2023
12 newest of 14 All 14 (JSON)