Today the infrastructure needed to support pervasive computing and the Internet of Things (IoT) is unparalleled as entirely new classes of applications and systems emerge. For example, pervasive systems designed to augment human cognition with tasks such as face recognition must operate at “superhuman speeds,” delivering insights to help with human decision-making within very strict and narrow time limits. Similarly, the emergence of pervasive video analytics demands processing of very large volumes of video data in near-real-time. In general, the field of pervasive computing is rapidly changing in the face of major advances in sensing, data processing techniques, and wearable computing. The ever increasing data rates of high-speed networks also factor into the design tradeoff to decide if computing should be local, or remote.

中文翻译：

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边缘普及计算

如今，随着全新的应用程序和系统类别的出现，支持普适计算和物联网（IoT）所需的基础架构已无与伦比。例如，旨在通过诸如面部识别之类的任务增强人类认知的普适系统必须以“超人类的速度”运行，在非常严格且狭窄的时限内提供洞察力，以帮助人类做出决策。同样，无处不在的视频分析技术的出现要求近乎实时地处理大量视频数据。通常，面对传感，数据处理技术和可穿戴计算的重大进步，普适计算领域正在迅速变化。高速网络不断增长的数据速率也影响了设计权衡，以决定计算是本地的还是远程的。