The development of cloud, fog, and edge computing has led to great advances in reducing latency and saving bandwidth, and these methods have therefore been broadly applied in various domains, including healthcare, transportation, and the Internet of Things (IoT). Traditional edge computing solutions have proven to be insufficient in fulfilling the demanding prerequisites of low latency and high data rates. Additionally, publicly available edge cloud solutions fail to meet the required standards for ensuring privacy protection. Consequently, Private Edge Cloud Systems (PECSs) have garnered attention as a prospective solution owing to their capacity to mitigate privacy risks and their significant computing capacity. PECS research has seen significant growth, but there is a lack of detailed review of its issues, approaches, and applications in the literature. To explore the potential application value of PECS, this paper provides a systematic review of intelligent platforms and architecture for PECSs. Specifically, an overview of the fundamental characteristics of PECSs is provided. Second, we classify intelligent platforms and architectures and analyze their implementation techniques and realization methods. Third, we discuss four specific application scenarios. Finally, promising future research directions are discussed. The findings of this research show that PECSs can effectively meet the requirements for low latency and privacy protection and are a fertile domain for further research.

中文翻译：

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私有边缘云系统的智能架构和平台：回顾


云、雾和边缘计算的发展在减少延迟和节省带宽方面取得了巨大进步，因此这些方法被广泛应用于各个领域，包括医疗保健、交通和物联网（IoT）。事实证明，传统的边缘计算解决方案不足以满足低延迟和高数据速率的苛刻先决条件。此外，公开的边缘云解决方案无法满足确保隐私保护所需的标准。因此，私有边缘云系统（PECS）因其降低隐私风险的能力和强大的计算能力而作为一种潜在的解决方案而受到关注。 PECS 研究有了显着的增长，但文献中缺乏对其问题、方法和应用的详细回顾。为了探索PECS的潜在应用价值，本文对PECS的智能平台和架构进行了系统综述。具体来说，提供了 PECS 基本特征的概述。其次，对智能平台和架构进行分类，分析其实现技术和实现方法。第三，我们讨论四个具体的应用场景。最后，讨论了有前景的未来研究方向。本研究结果表明，PECS能够有效满足低延迟和隐私保护的要求，是进一步研究的沃土。