Distributed computing frameworks offer a powerful means to train AI models and deploy AI applications at scale. This reprint aims to introduce those recent advances and practical applications in distributed computing. This reprint presents the most recent research in distributed computing, with a particular emphasis on studies that feature practical methods and experimental results. It aims to help readers quickly grasp emerging trends in the field. In particular, this reprint can assist readers in identifying effective mechanisms to address the challenges they encounter in distributed computing. Much of the content in this reprint is drawn from New Advances in Distributed Computing and Its Applications, a Special Issue of MDPI's journal Electronics. This Special Issue includes 20 papers, covering topics such as artificial intelligence model offloading in mobile networks, blockchain-based data security, throughput optimization for distributed blockchain systems, and resource scheduling in FPGA systems for edge computing. We have selected the most relevant papers and organized them into four chapters based on their themes.

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