mlsanityData to 14 Oct 2026

Deep Learning in the Era of Edge Computing: Challenges and Opportunities

arXiv 2010.08861 ↗First posted 17 Oct 2020cs.LGcited by 10

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Abstract (arXiv)

The era of edge computing has arrived. Although the Internet is the backbone of edge computing, its true value lies at the intersection of gathering data from sensors and extracting meaningful information from the sensor data. We envision that in the near future, majority of edge devices will be equipped with machine intelligence powered by deep learning. However, deep learning-based approaches require a large volume of high-quality data to train and are very expensive in terms of computation, memory, and power consumption. In this chapter, we describe eight research challenges and promising opportunities at the intersection of computer systems, networking, and machine learning. Solving those challenges will enable resource-limited edge devices to leverage the amazing capability of deep learning. We hope this chapter could inspire new research that will eventually lead to the realization of the vision of intelligent edge.

Key facts. Cited by 10 papers in the map (data through 14 Oct 2026). First posted on arXiv 17 Oct 2020.

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Citing papers per year: 2021: 4; 2022: 2; 2023: 1; 2024: 1; 2025: 1; 2026: 1.

10 papers.