Multi-level Optimization of Shared Cloud Architecture for Computer-Supported Sports Collaborative Learning Experiment Scenario
Decao Shao, Bin Feng, Gao Guocai · 2022 7th International Conference on Communication and Electronics Systems (ICCES) · 2022
Multi-level optimization of the shared cloud architecture for the computer-supported sports collaborative learning experiment scenario is studied in the paper. Incremental checkpointing can also reduce the size of the checkpoint file, thereby reducing the overhead of saving checkpoints. The implementation of incremental checkpoints relies on a runtime monitor. If the monitor finds that a certain storage area has not been modified since the last checkpoint during a checkpoint, it will be ignored in the current checkpoint. This memory area can reduce the size of the current checkpoint file. IaaS cloud computing platform mainly provides users with basic resource services in three aspects: computer, storage, and network. Hence, with this model, the designed optimization of shared cloud architecture for the computer-supported sports collaborative learning experiment scenario is demonstrated. Through the experimental results, the performance is validated.