Scalable Task Scheduling and Management Orchestration in Distributed Edge-Cloud Systems

The evolution from the Internet of Things (IoT) to the Internet of Everything (IoE) has significantly increased the demand for high computational resources. As a result of this technological advancement, an integration of centralized cloud and edge computing resources known as the Cloud-Edge Continuum (CEC), or digital continuum is required to meet current computational demands. CEC leverages the scalability of cloud infrastructure and the low-latency processing capabilities of edge devices to support highly interconnected and adaptive communication systems. This integration is critical for the seamless convergence of macro, micro, and pico networks with Non-Terrestrial Networks (NTNs) in 6G environments. Traditionally, CEC environments rely on centralized cloud orchestrators to manage the resource pool across the continuum. However, this approach often results in inefficient resource management and poor adaptability to the dynamic nature of CEC workloads and environments. To address these challenges, this research proposes a Distributed Intelligent Management and Orchestration (DIMO) framework aimed at improving resource management efficiency and adaptability within the edge continuum.