AI-Driven Edge and Cloud Computing for IoT

Dear Colleagues,

The Internet of Things (IoT) has emerged as a transformative technology, revolutionizing the way we live, work, and interact with our environment. IoT systems generate and transmit massive volumes of data that should be efficiently filtered, analyzed, and processed to extract actionable insights. Effective communication between connected devices requires high reliability, low latency, and robust scalability. In this context, 5G networks offer not only significantly higher data rates but also ultra-low-latency communication, making them ideal for critical IoT applications that require real-time responsiveness and exceptional reliability. A key enabler within 5G is Machine-Type Communications (MTC), which supports seamless connectivity among devices and is widely adopted by mobile network operators, equipment manufacturers, and MTC service providers. However, the increasing demands for high traffic capacity, low-latency transmission, and deterministic service delivery, particularly in IoT communications, necessitate a fundamental shift in current communication and networking architectures. To address these challenges, cloud and edge computing paradigms have been introduced as complementary solutions to alleviate the processing burden on centralized systems. By enabling distributed data processing closer to the data sources, cloud/edge-enabled IoT architectures significantly reduce latency and network congestion. This proximity-aware computing not only enhances support for real-time, latency-sensitive applications, but also strengthens data security and privacy by minimizing unnecessary data transmission across the network.

The scope of this Special Issue includes, but is not limited to,

• AI-driven resource management and scheduling across edge and cloud networks for IoT;
• Collaborative intelligence between edge and cloud networks for IoT;
• Lightweight and distributed learning for IoT;
• Edge intelligence for real-time sensing, control, and decision-making for IoT;
• Security, privacy, and trust mechanisms in AI-enabled edge and cloud computing for IoT;
• Energy-efficient and sustainable computing architectures for IoT;
• IoT applications in smart cities, autonomous systems, industry, and healthcare.

Dr. Xiaonan Liu
Dr. Yao Sun
Guest Editors

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