IoT (物聯網) 的邊緣分析
Edge Analytics in IoT
|出版日期||內容資訊||英文 17 Pages; 11 Tables; 4 Charts
|IoT (物聯網) 的邊緣分析 Edge Analytics in IoT|
|出版日期: 2015年04月13日||內容資訊: 英文 17 Pages; 11 Tables; 4 Charts||
本報告提供邊緣運算 (Edge Computing)，尤其是邊緣分析 (Edge Analytics) 的概念與未來性市場趨勢分析，提供您IoT情報功能的3個階段，在其中邊緣分析在IoT資料分析上所達成的作用，邊緣分析的普及促進·阻礙因素，目前市場主要趨勢·趨勢，彙整IoT相關設備 (連網型·設備) 所產生·理解·轉送的資料數量預測，主要技術供應商的邊緣分析措施 (相關產品與服務·解決方案等) 等資訊。為您概述為以下內容。
In ABI Research's view, one of the most significant trends in the Internet of Things (or the connected world-the Internet of Everything-as a whole) is the shifting balance between edge computing and cloud computing. The early days of the IoT and its conceptual precursor, M2M, have been characterized by the critical role of cloud platforms as application enablers. Intelligent systems have largely relied on the cloud level for their intelligence, and the actual devices of which they consist have been relatively unsophisticated. This old premise is currently being shaken up, as the computing capabilities on the edge level advance faster than those of the cloud level. ABI Research refers to this trend as a paradigm shift-from the connected device paradigm to the intelligent device paradigm. This is, most of all, making the available architecture choices more nuanced and allowing organizations deploying the IoT to enhance their physical assets and processes in novel ways. Edge computing, also known as edge intelligence, is what is driving this shift.
This study explores edge computing specifically as an analytic proposition: as an approach to analyze data close to its source instead of sending it to a remote server for cloud-level analysis. The report builds on ABI Research's earlier work on IoT analytics, aiming to provide further insight and conceptual clarity on the role of the network edge in the IoT. Its first section summarizes the three levels of IoT intelligence, and provides commentary on the related drivers and inhibitors. Also, the most noteworthy market trends and observations are listed under this section. The second section, in the meantime, includes quantitative analyses of the "data universe" associated with the IoT: providing forecasts on the data volumes that are (a) generated, (b) captured, and (c) transmitted by connected devices. Finally, the report's third section serves as an overview of a number of technology vendors that are pioneering edge analytics with their products, services, and solutions.