Abstract
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.
I. INTRODUCTION
In the next decades, Internet of Things (IoT), the interconnected networks of physical objects embedded with electronics, software, sensors, and connectivity will revolutionize how we work, live, exercise, entertain, and travel. IoT is experiencing explosive growth in both quantities (20.8 billion IoT devices by 2020 [1]) and utility with increasingly important applications in healthcare, military operations, transportation, and urban planning [2]. However, IoT faces several major growing challenges. First, incorporating appropriate intelligence and smart connectivity into IoT objects requires a computing paradigm that exceeds the current computing capabilities of smart phones and portables [3].
V. CONCLUSION
The existing cloud-centric architecture of IoT poses serious challenges regarding cognitive capacity, connectivity, safety, privacy, flexibility, latency, and energy-efficiency. We have presented the COGNICOM+ concept, a brain-inspired software-hardware paradigm, to support IoT’s future growth. Consisting of the cognitive engine and the smart connectivity, COGNICOM+ brings computing closer to end-user and focuses on optimal uses of local SAG and cloud computing. The CE is powered by deep learning algorithms integrated with game-theoretic decision analytics, implemented on low power ASICs. It provides cognitive functions to smart objects.
