边缘智能创新架构、挑战和解决方案的评估

Heikku Siltanen, Lars Vlrtanen
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引用次数: 3

摘要

在数据收集地附近进行数据收集、缓存、分析和处理被称为“边缘智能”,这是一组相互关联的设备和系统。边缘智能旨在提高数据处理的质量和速度,同时保护数据的隐私和安全。这一研究领域始于2011年,尽管相对年轻,但在过去五年中取得了巨大的发展。本文综述了边缘智能的架构(基于数据放置的架构以减少延迟;2)基于编排的eca——物联网。3)基于大数据分析的架构;4)基于安全的架构)以及边缘智能创新架构的挑战和解决方案。
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Assessment of Innovative Architectures, Challenges and Solutions of Edge Intelligence
Data collecting, caching, analysis, and processing in close proximity to where the data is collected is referred to as "edge intelligence," a group of linked devices and systems. Edge Intelligence aims to improve data processing quality and speed while also safeguarding the data's privacy and security. This area of study, which dates just from 2011, has shown tremendous development in the last five years, despite its relative youth. This paper provides a survey of the architectures of edge intelligence (Data Placement-Based Architectures to Reduce Latency; 2) Orchestration-Based ECAs- IoT. 3) Big Data Analysis-Based Architectures; and 4) Security-Based Architectures) as well as the challenges and solutions for innovative architectures in edge intelligence.
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