认知计算与通信:物联网云的补充解决方案

Van-Tam Nguyen, Nhan Nguyen-Thanh, Lita Yang, D. Nguyen, C. Jabbour, B. Murmann
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引用次数: 6

摘要

物联网(IoT)正在经历设备和应用数量的爆炸式增长。然而,现有的以云为中心的物联网架构在网络延迟、隐私和能效方面提出了严峻的挑战。我们提出了COGNICOM+概念,这是一种以大脑为灵感的软硬件范式,以支持物联网的未来发展,并在COGNICOM+中开发了4个研究方向-灵活无线电,卷积神经网络加速器,压缩深度学习和推理与协作博弈论。其关键思想是使计算更接近最终用户,同时专注于本地智能应用网关和云计算的最佳使用。COGNICOM+由两个关键组件组成:认知引擎(CE)和智能连接(SC)。认知引擎由深度学习算法与博弈论决策分析相结合,在低功耗特定应用集成电路上实现。它为智能对象提供认知功能。智能连接集成了认知无线电、收发器和基带处理器的神经网络设计。SC为物联网对象提供灵活可靠的连接,优化分配通信资源。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Cognitive computation and communication: A complement solution to cloud for IoT
The Internet of Thing (IoT) is experiencing explosive growth in the number of devices and applications. However, the existing cloud-centric architecture of IoT poses serious challenges regarding network latency, privacy, and energy-efficiency. We have presented COGNICOM+ concept, a brain-inspired software-hardware paradigm, to support IoT's future growth and developed 4 research directions - flexible radio, convolutional neural network accelerator, compressed deep learning, and game theory for reasoning and collaboration - within COGNICOM+. The key idea is to bring computing closer to the end-user while focusing on optimal uses of local smart application gateway and cloud computing. COGNICOM+ consists of two key components: Cognitive Engine (CE) and Smart Connectivity (SC). The cognitive engine is powered by deep-learning algorithms integrated with game-theoretic decision analytics, implemented on a low-power application-specific integrated circuit. It provides cognitive functions to smart objects. The smart connectivity integrates neural network inspired designs of cognitive radio, transceivers, and baseband processors. The SC provides flexible and reliable connections to IoT objects and optimally distributes communication resources.
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