In the present era of research and technology, several emerging concepts like Wireless Sensor Networks, Body Wireless Sensor Networks, Fog, Edge, and Big Data Analytics can support the design and development of intelligent systems in diverse domains, e.g., transportation, education, enterprise, and industry, etc. Wireless sensor network technologies are one of the key research areas in computer science. Artificial Intelligence, Intelligent Computing Techniques, and Deep Learning are offering practical tools for many engineering applications. Recent Intelligent Computing Techniques have provided unexpected solutions for wireless network applications. Wireless network applications, such as real-time traffic data, sensor data from driverless cars, or entertainment streaming recommendations, generate enormous quantities of data for real-time collection and processing. These requirements can only be met through the integration of artificial intelligence (AI) and deep learning techniques in wireless infrastructure and end-user devices.

The objective of this Special Issue is to explore Intelligent Computing Techniques to address practical challenges in wireless networks. We hope to bring researchers and academics together to present their latest work on network modeling and architecture, networking applications, security and privacy, load balancing, and various challenges related to the design of future wireless networks using AI and deep learning methods.

We solicit the submission of high-quality original research and review articles closely related to the following topics, particularly interdisciplinary submissions that bring together next-generation Intelligence of Things (IoT), IoT security, 5G and IoT for communication systems, social networks, delay tolerant networks, wireless sensor networks, vehicular networks, and other new topics about wireless communications and networking.

Potential topics include but are not limited to the following:

• Intelligent Computing Techniques-based mobile network design
• Intelligent Computing Techniques for wireless network applications
• Innovative intelligent computing architecture/algorithms for wireless networks
• Edge computing using AI for QoS provisioning in wireless networks
• Resource allocation for shared/virtualized networks using machine learning
• High performance computing systems for applications in autonomous driving, healthcare, and recommendation
• The physical environment, both local and remote sensors
• Intelligent Computing Techniques in industrial-level systems
• AI techniques and optimization algorithms for real life applications
• AI-based resource allocation, optimization, and energy-efficient networking techniques
• AI-driven cloud/fog-assisted wireless communications
• Big-data intelligent analytic frameworks for networking data
• Deep learning methods for applications in object detection and identification, object tracking, human action recognition, cross-modal and multimodal data analysis