The proliferation of Internet of Things (IoT) devices and the exponential growth of generated data demand innovative frameworks capable of providing ultra-low latency, high reliability, and intelligent processing. Integration of sixth-generation (6G) wireless networks with edge computing offers a transformative solution, enabling real-time data analytics, distributed intelligence, and seamless connectivity in ultra-dense IoT environments. This chapter presents a comprehensive analysis of the architectural design, key enabling technologies, and performance advantages of 6G-edge computing frameworks for next-generation IoT applications. Industrial automation, remote healthcare, smart cities, and immersive AR/VR services are examined to highlight the practical implications of such integration. Critical challenges, including resource management, energy efficiency, interoperability, and security, are discussed alongside potential AI-driven solutions to enhance system resilience and scalability. The study emphasizes the synergy between 6G communication capabilities and localized edge intelligence as a foundation for enabling intelligent, efficient, and sustainable IoT ecosystems.
The rapid expansion of the Internet of Things (IoT) has led to the deployment of billions of interconnected devices generating massive volumes of heterogeneous data [1]. Modern IoT ecosystems span multiple domains, including industrial automation, healthcare, transportation, smart cities, and environmental monitoring, each with unique requirements for latency, reliability, and computational capability [2]. Conventional cloud-centric architectures struggle to support the performance needs of such large-scale and data-intensive environments [3]. High network congestion, delayed processing, and bandwidth limitations hinder real-time data analysis, predictive decision-making, and autonomous operations [4]. Addressing these challenges requires a paradigm shift in both communication and computation infrastructure, moving toward distributed, intelligent, and low-latency frameworks capable of accommodating the demands of next-generation IoT applications [5].
The evolution of wireless communication technology has progressed from 4G to 5G, enhancing data rates, network coverage, and reliability [6]. These improvements, 5G networks face inherent limitations when handling ultra-dense IoT environments and latency-critical applications [7]. The emerging sixth-generation (6G) networks are poised to overcome these constraints by offering terabit-per-second data rates, ultra-low latency in sub-millisecond ranges, massive device connectivity, and AI-driven network management [8]. Features such as terahertz communication, massive multiple-input multiple-output (MIMO) systems, and intelligent spectrum utilization will significantly enhance the efficiency and reliability of IoT networks [9]. 6G networks will facilitate seamless connectivity across heterogeneous devices, enabling real-time communication for mission-critical services such as autonomous transportation systems, remote surgeries, and industrial robotic operations, which demand high precision and reliability [10].
Edge computing complements high-speed wireless communication by relocating computational resources closer to data sources [11]. This paradigm reduces dependence on centralized cloud infrastructure, minimizes latency, alleviates network congestion, and supports localized data analytics [12]. By enabling real-time processing and decision-making at the network edge, edge computing enhances the responsiveness and operational efficiency of IoT systems [13]. Distributed intelligence at edge nodes allows predictive and adaptive analytics to occur close to the source, which was particularly important for applications that require immediate responses, such as industrial automation, AR/VR services, and smart healthcare monitoring [14]. Integrating edge computing with 6G networks creates a synergistic framework that combines high-speed communication with low-latency localized processing, forming the foundation for intelligent and scalable IoT ecosystems [15].
