mlsanityData to 7 Oct 2026

Challenges and Opportunities in Edge Computing

arXiv 1609.01967 ↗First posted 7 Sep 2016cs.DCcited by 26

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Abstract (arXiv)

Many cloud-based applications employ a data centre as a central server to process data that is generated by edge devices, such as smartphones, tablets and wearables. This model places ever increasing demands on communication and computational infrastructure with inevitable adverse effect on Quality-of-Service and Experience. The concept of Edge Computing is predicated on moving some of this computational load towards the edge of the network to harness computational capabilities that are currently untapped in edge nodes, such as base stations, routers and switches. This position paper considers the challenges and opportunities that arise out of this new direction in the computing landscape.

Key facts. Cited by 26 papers in the map (data through 7 Oct 2026). First posted on arXiv 7 Sep 2016.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 2; 2022: 4; 2023: 9; 2024: 6; 2025: 3; 2026: 2.

26 papers.

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  1. 2022No One Left Behind: Inclusive Federated Learning over Heterogeneous Devicescited by 36
  2. 2023FedRA: A Random Allocation Strategy for Federated Tuning to Unleash the Power of Heterogeneous Clientscited by 18
  3. 2024Training Machine Learning models at the Edge: A Surveycited by 11
  4. 2021Anomaly Detection using Edge Computing in Video Surveillance System: Reviewcited by 6
  5. 2022BED: A Real-Time Object Detection System for Edge Devicescited by 6
  6. 2023AdapterFL: Adaptive Heterogeneous Federated Learning for Resource-constrained Mobile Computing Systemscited by 4
  7. 2024Adaptive Deep Learning for Efficient Visual Pose Estimation aboard Ultra-low-power Nano-dronescited by 4
  8. 2023FLEdge: Benchmarking Federated Machine Learning Applications in Edge Computing Systemscited by 3
  9. 2023Task Offloading for Smart Glasses in Healthcare: Enhancing Detection of Elevated Body Temperaturecited by 3
  10. 2024Real-Time Compressed Sensing for Joint Hyperspectral Image Transmission and Restoration for CubeSatcited by 3
  11. 2023A Constant-per-Iteration Likelihood Ratio Test for Online Changepoint Detection for Exponential Family Modelscited by 2
  12. 2023Enhancing Trustworthiness in ML-Based Network Intrusion Detection with Uncertainty Quantificationcited by 2
14 more
  1. 2024From Algorithm to Hardware: A Survey on Efficient and Safe Deployment of Deep Neural Networkscited by 2
  2. 2025LLMPi: Optimizing LLMs for High-Throughput on Raspberry Picited by 2
  3. 2021Multi-task learning on the edge: cost-efficiency and theoretical optimalitycited by 1
  4. 2022PFGE: Parsimonious Fast Geometric Ensembling of DNNscited by 1
  5. 2023On Achieving Privacy-Preserving State-of-the-Art Edge Intelligencecited by 1
  6. 2024Rapid Deployment of DNNs for Edge Computing via Structured Pruning at Initializationcited by 1
  7. 2024An Edge Computing-Based Solution for Real-Time Leaf Disease Classification using Thermal Imagingcited by 1
  8. 2026TinyML-Enabled IoT for Sustainable Precision Irrigationcited by 1
  9. 2022Introducing Federated Learning into Internet of Things ecosystems -- preliminary considerationscited by 0
  10. 2023Automated Speaker Independent Visual Speech Recognition: A Comprehensive Surveycited by 0
  11. 2023Quantized Non-Volatile Nanomagnetic Synapse based Autoencoder for Efficient Unsupervised Network Anomaly Detectioncited by 0
  12. 2025An End to End Edge to Cloud Data and Analytics Strategycited by 0
  13. 2025A Hybrid Proactive And Predictive Framework For Edge Cloud Resource Managementcited by 0
  14. 2026Robust Spiking Neural Networks Against Adversarial Attackscited by 0