Special Issue "Intelligent Computing System Models and Designs for IoT"

Submission Deadline: 28 February 2021 (closed)
Guest Editors
Prof. Danda B. Rawat, Howard University, USA
Prof. Sumarga Kumar Sah Tyagi, Zhongyuan University of Technology, China
Prof. Imran Shafique Ansari, University of Glasgow, U.K.

Summary

The evolution of computing in future networks presents new exploration areas for industry practitioners and academic researchers. The development and deployment of intelligence computing is paving the way for the Internet of Things (IoT) paradigm. Artificial intelligence and machine learning approaches to intelligent computing have led to energy-efficient solutions at different levels and layers such as data processing, resource optimization, and analytics. The implementation of computational services using various ubiquitous computing models constitute conventional methodologies as well as modern state-of-the-art systems and global networking infrastructure.


Technologies such as edge computing, fog computing, information-centric network, and content-centric networks address communication and networking issues for ambient intelligence and applications. With a broad direction of IoT, from smart cities to smart industry, computational intelligence and development need attention; especially dealing with challenges relating to scalable computing, resource optimization, low energy consumption, robust network architecture, and other ubiquitous intelligence.

 

The special issue focusses on the models and designs of energy-efficient intelligent computing systems along with its state-of-art architecture, methodologies, and computational resource optimization for IoT. Further, the special issue will also focus on the theory and research practices of neural networks, deep learning, and big data analytics for the physical layer in IoT applications. The business and managerial implications of such systems and architecture are also of interest.


Keywords
• Intelligent computing system models for IoT.
• AI-based computing system framework designs for IoT.
• Energy-efficient computing system models and designs for IoT.
• Physical layer communications, networking, data management using AI for IoT.
• Protocols designs for energy harvesting intelligent computing for IoT.
• Content centric and information-centric network designs for smart cities.
• Scalable intelligent computing for distributed middleware in IoT.
• AI-based Big data analytics and resource optimization models for IoT applications.
• ML/DL-based computation models for physical communication in IoT.
• Intelligent multicasting models for IoT applications.
• Performance analysis and resource management in IoT.
• Intelligent computing models and designs for smart industries.
• Business and managerial implications of smart computation models and designs.