[论文解读] The Power of Internet of Things (IoT): Connecting the Dots with Cloud, Edge, and Fog Computing

Shams Forruque Ahmed, Shanjana Shuravi+4 more|arXiv (Cornell University)|Sep 7, 2023

IoT and Edge/Fog Computing被引用 4

一句话总结

本文全面回顾了物联网与云、边缘及雾计算的集成，分析了它们之间的协同效应、比较优势及局限性。研究表明，通过结合这三种架构，可实现可扩展、低延迟的物联网系统，利用云资源进行存储与处理，边缘计算实现实时响应，雾计算降低延迟与带宽使用，从而为下一代智能应用铺平道路。

ABSTRACT

The Internet of Things (IoT) is regarded as an improved communication system that has revolutionized traditional lifestyles. To function successfully, IoT requires a combination of cloud, fog, and edge computing architectures. Few studies have addressed cloud, fog, and edge computing simultaneously, comparing them and their issues, although several studies have looked into ways of integrating IoT with either one or two computing systems. Thus, this review provides a thorough understanding of IoT integration with these three computing architectures, as well as their respective applications and limitations. It also highlights the advantages, unresolved issues, future opportunities and directions of IoT integration with the computing systems to advance the IoT. IoT can use the Cloud's almost limitless resources to overcome technology restrictions, such as data processing, storage, and transmission. While edge computing can outperform cloud computing in many circumstances, IoT and edge computing become increasingly integrated as IoT devices increase. Cloud computing also poses a few issues, including managing time-sensitive IoT applications like video gaming, simulation, and streaming, which can be addressed by fog computing integrated with IoT. Due to the proximity of fog computing resources to the edge, data transfers and communication delays to the cloud can be reduced as a result of combining the two. The integration of IoT with cloud, fog, and edge computing will create new business prototypes and opportunities. Since IoT has the potential to greatly enhance connectivity infrastructure as an inevitable component of the future internet, further study is needed before it can be fully integrated.

研究动机与目标

• 提供对物联网如何与云、边缘及雾计算架构集成的全面理解。
• 比较云、边缘及雾计算在物联网环境中的优势、局限性及权衡。
• 识别尚未解决的问题及推动物联网系统发展的未来研究方向。
• 突出联合云-边-雾架构在实现低延迟、可扩展且高效物联网应用方面的潜力。

提出的方法

• 对现有物联网与云、边缘及雾计算集成研究的系统性文献回顾。
• 对三类计算层级中的应用、用例及部署模式进行分类。
• 分析混合架构中延迟、带宽使用及处理效率等性能指标。
• 通过计算范式对比评估识别架构权衡。
• 映射跨层级存在的未解决问题，包括安全性、可扩展性及互操作性。
• 基于当前集成与标准化方面的差距，综合未来研究机会。

实验结果

研究问题

• RQ1 云、边缘及雾计算如何在支持物联网工作负载方面相互补充？
• RQ2 在物联网部署中，云、边缘及雾计算在关键性能方面有何差异及权衡？
• RQ3 在集成物联网与多层计算架构方面，存在哪些未解决的挑战？
• RQ4 与纯云或纯边缘解决方案相比，雾计算如何减少物联网系统中的延迟与带宽消耗？
• RQ5 在推进集成的云-边-雾物联网系统方面，哪些未来研究方向最具前景？

主要发现

• 云计算提供近乎无限的存储与处理能力，使其成为物联网系统中大规模数据分析与长期存储的理想选择。
• 边缘计算支持实时处理与低延迟响应，对视频流媒体和工业自动化等时间敏感型应用至关重要。
• 雾计算通过在数据源附近处理数据，减少了通信延迟与带宽使用，充当边缘设备与云之间的中间层。
• 将雾计算与边缘及云计算集成，显著提升了大规模物联网部署中的可扩展性与响应能力。
• 尽管具有优势，这三种范式在安全性、互操作性及动态资源管理方面仍面临未解决的挑战。
• 未来的物联网系统很可能依赖于混合的云-边-雾架构，以平衡性能、成本与可靠性。