Edge Intelligence: Paving the Last Mile of Artificial Intelligence With Edge Computingстатья из журнала
Аннотация: With the breakthroughs in deep learning, the recent years have witnessed a booming of artificial intelligence (AI) applications and services, spanning from personal assistant to recommendation systems to video/audio surveillance. More recently, with the proliferation of mobile computing and Internet of Things (IoT), billions of mobile and IoT devices are connected to the Internet, generating zillions bytes of data at the network edge. Driving by this trend, there is an urgent need to push the AI frontiers to the network edge so as to fully unleash the potential of the edge big data. To meet this demand, edge computing, an emerging paradigm that pushes computing tasks and services from the network core to the network edge, has been widely recognized as a promising solution. The resulted new interdiscipline, edge AI or edge intelligence (EI), is beginning to receive a tremendous amount of interest. However, research on EI is still in its infancy stage, and a dedicated venue for exchanging the recent advances of EI is highly desired by both the computer system and AI communities. To this end, we conduct a comprehensive survey of the recent research efforts on EI. Specifically, we first review the background and motivation for AI running at the network edge. We then provide an overview of the overarching architectures, frameworks, and emerging key technologies for deep learning model toward training/inference at the network edge. Finally, we discuss future research opportunities on EI. We believe that this survey will elicit escalating attentions, stimulate fruitful discussions, and inspire further research ideas on EI.
Год издания: 2019
Авторы: Zhi Zhou, Xu Chen, En Li, Liekang Zeng, Ke Luo, Junshan Zhang
Издательство: Institute of Electrical and Electronics Engineers
Источник: Proceedings of the IEEE
Ключевые слова: IoT and Edge/Fog Computing, Advanced Neural Network Applications, Privacy-Preserving Technologies in Data
Другие ссылки: Proceedings of the IEEE (PDF)
Proceedings of the IEEE (HTML)
arXiv (Cornell University) (PDF)
arXiv (Cornell University) (HTML)
Proceedings of the IEEE (HTML)
arXiv (Cornell University) (PDF)
arXiv (Cornell University) (HTML)
Открытый доступ: bronze
Том: 107
Выпуск: 8
Страницы: 1738–1762