IEEE Network· 2018Q1
Learning IoT in Edge: Deep Learning for the Internet of Things with Edge Computing
- 1,583citations
- Q1SCImago
- 2018year
Short summary
A novel offloading strategy optimizes deep learning tasks for IoT devices in edge computing environments, outperforming existing solutions.
AI-generated from the title and abstract; the full text is not read.
Key points
- Deep learning is suitable for extracting information from IoT sensor data and for edge computing environments.
- A novel offloading strategy is designed to optimize the performance of IoT deep learning applications within edge computing.
- The proposed strategy addresses the limited processing capabilities of existing edge nodes.
- Performance evaluations show the method outperforms other optimization solutions for deep learning in IoT.
AI-generated from the title and abstract; the full text is not read.
Abstract
Deep learning is a promising approach for extracting accurate information from raw sensor data from IoT devices deployed in complex environments. Because of its multilayer structure, deep learning is also appropriate for the edge computing environment. Therefore, in this article, we first introduce deep learning for IoTs into the edge computing environment. Since existing edge nodes have limited processing capability, we also design a novel offloading strategy to optimize the performance of IoT deep learning applications with edge computing. In the performance evaluation, we test the performance of executing multiple deep learning tasks in an edge computing environment with our strategy. The evaluation results show that our method outperforms other optimization solutions on deep learning for IoT.
The authors' abstract, as published at the source. IEEE Network, 2018 · DOI ↗
Continue with a free account
Ask the paper: 3 free questions a day about this paper; save it, get its citation, new summaries every day for your field. Takeaways are Premium.
Continue free on the webSign in with Google or Apple; no card needed. You come back to this paper.
On your phone:
Field: Computer Networks and Communications
Computer Networks and CommunicationsComputer Science