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    Li Zhenhua, Wang Hongyi, Li Yang, Lin Hao, Yang Xinlei. Cloud Native Reinforced Design for Large-Scale Complex Terminal Networks[J]. Journal of Computer Research and Development, 2024, 61(1): 2-19. DOI: 10.7544/issn1000-1239.202330726
    Citation: Li Zhenhua, Wang Hongyi, Li Yang, Lin Hao, Yang Xinlei. Cloud Native Reinforced Design for Large-Scale Complex Terminal Networks[J]. Journal of Computer Research and Development, 2024, 61(1): 2-19. DOI: 10.7544/issn1000-1239.202330726

    Cloud Native Reinforced Design for Large-Scale Complex Terminal Networks

    • As the “last mile” of Internet content delivery, terminal networks seem rather simple but in fact constitute 99% of the performance bottlenecks. Classic design is usually oriented to typical devices and regular environments, thus making it difficult to accommodate and reproduce diversified scenarios and resulting in severe performance degradation. By comprehensively gathering and deeply diagnosing the anomalies of large-scale complex terminal networks at the cloud, we have revealed several important defects of the classic design for terminal networks in three key dimensions—availability, reliability and credibility. In order to fix these defects effectively and efficiently, the cross-layer and cross-technology collaboratively reinforced design methodology is adopted (e.g., the time-inhomogeneous 4G/5G dual connectivity management method is utilized to minimize the probability of network disconnection), so as to fulfill self-regulation mechanism design for ubiquitous scenarios. The research achievements have been applied to the high-speed network of the Ministry of Public Security, 17 million UUSpeedTest App users, 70 million Xiaomi mobile phones, 100 million Baidu PhoneGuard users, and 900 million WiFi devices. In recent years, we have also conducted forward-looking network design based on cloud-hosted emulators to discover and fix potential defects without real-world user engagement, thus making the design of terminal networks “born in the cloud and grow in the cloud”. The research achievements have been applied to Huawei DevEco Studio IDE (Integrated Development Environment), Tencent App Market, Google Android Emulator, and multiple popular Apps (like Douyin and Toutiao) of ByteDance.
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