DCAIOct 24, 2022

Deep Edge Intelligence: Architecture, Key Features, Enabling Technologies and Challenges

arXiv:2210.12944v11 citationsh-index: 8
Originality Incremental advance
AI Analysis

This proposes a new paradigm for delivering AI services at the network edge, potentially impacting billions of connected devices and users, though it is conceptual and incremental in combining existing technologies.

The paper introduces Deep Edge Intelligence (DEI), a computing vision that integrates deep learning, AI, cloud/edge computing, 5G/6G, IoT, and microservices to provide reliable and secure intelligence services globally, aiming to enhance user experience.

With the breakthroughs in Deep Learning, recent years have witnessed a massive surge in Artificial Intelligence applications and services. Meanwhile, the rapid advances in Mobile Computing and Internet of Things has also given rise to billions of mobile and smart sensing devices connected to the Internet, generating zettabytes of data at the network edge. The opportunity to combine these two domains of technologies to power interconnected devices with intelligence is likely to pave the way for a new wave of technology revolutions. Embracing this technology revolution, in this article, we present a novel computing vision named Deep Edge Intelligence (DEI). DEI employs Deep Learning, Artificial Intelligence, Cloud and Edge Computing, 5G/6G networks, Internet of Things, Microservices, etc. aiming to provision reliable and secure intelligence services to every person and organisation at any place with better user experience. The vision, system architecture, key layers and features of DEI are also detailed. Finally, we reveal the key enabling technologies and research challenges associated with it.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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