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This book focuses on the challenges and solutions for scheduling tasks in distributed cloud and edge computing systems, with a particular emphasis on predicting workload and resources and optimizing performance and resource utilization through innovative algorithms and methodologies. The book provides an in-depth exploration of theoretical and practical aspects across seven comprehensive parts. The book first introduces the key concepts of cloud computing, edge computing, and their convergence in distributed cloud-edge systems. The authors then lay the groundwork for understanding workload prediction, energy management, and integrating cloud-edge infrastructures with large artificial intelligence (AI) models. The book then presents a detailed examination of workload and resource prediction techniques. Next, task scheduling is explored with a focus on energy efficiency and performance in unmanned aerial vehicles (UAVs), satellite-terrestrial edge networks, etc. The book also delves into integrating large-scale AI models within cloud-edge systems and introduces innovative practices of new infrastructure in cloud-edge systems. Finally, real-world applications of distributed…

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