Back to Search
Start Over
Deep Learning in the Era of Edge Computing: Challenges and Opportunities
- Source :
- Fog Computing
- Publication Year :
- 2020
-
Abstract
- 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, the 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.
- Subjects :
- FOS: Computer and information sciences
Multitenancy
Computer Science - Machine Learning
Edge device
business.industry
Computer science
Intersection (set theory)
Deep learning
Data science
Machine Learning (cs.LG)
Leverage (negotiation)
The Internet
Artificial intelligence
Enhanced Data Rates for GSM Evolution
business
Edge computing
Subjects
Details
- Language :
- English
- Database :
- OpenAIRE
- Journal :
- Fog Computing
- Accession number :
- edsair.doi.dedup.....6ba8bfd99ddb2fbaa372f755a48445e5