[论文解读] Fog Computing for Sustainable Smart Cities: A Survey

Charith Perera, Yongrui Qin+3 more|arXiv (Cornell University)|Mar 21, 2017

IoT and Edge/Fog Computing参考文献 54被引用 93

一句话总结

评估雾计算（边缘计算）如何补充云计算以构建可持续的物联网驱动的智慧城市，概述用例、雾计算的关键特征、比较与未解决的挑战。

ABSTRACT

The Internet of Things (IoT) aims to connect billions of smart objects to the Internet, which can bring a promising future to smart cities. These objects are expected to generate large amounts of data and send the data to the cloud for further processing, specially for knowledge discovery, in order that appropriate actions can be taken. However, in reality sensing all possible data items captured by a smart object and then sending the complete captured data to the cloud is less useful. Further, such an approach would also lead to resource wastage (e.g. network, storage, etc.). The Fog (Edge) computing paradigm has been proposed to counterpart the weakness by pushing processes of knowledge discovery using data analytics to the edges. However, edge devices have limited computational capabilities. Due to inherited strengths and weaknesses, neither Cloud computing nor Fog computing paradigm addresses these challenges alone. Therefore, both paradigms need to work together in order to build an sustainable IoT infrastructure for smart cities. In this paper, we review existing approaches that have been proposed to tackle the challenges in the Fog computing domain. Specifically, we describe several inspiring use case scenarios of Fog computing, identify ten key characteristics and common features of Fog computing, and compare more than 30 existing research efforts in this domain. Based on our review, we further identify several major functionalities that ideal Fog computing platforms should support and a number of open challenges towards implementing them, so as to shed light on future research directions on realizing Fog computing for building sustainable smart cities.

研究动机与目标

• 界定雾计算及其在智慧城市物联网中的作用。
• 识别雾计算与云计算相比的优点与局限性。
• 提出用例场景以推导雾平台的功能需求。
• 识别雾计算的十大关键特征及常见功能。
• 比较现有研究工作并突出差距与未来方向。

提出的方法

• 回顾现有的雾计算文献与先前的综述。
• 在智慧农业、交通、卫生、废物管理、水、温室气体、电网和零售等领域描述用例场景。
• 通过分析场景和文献来识别特征的分类体系。
• 综合适用于雾平台的主要功能，并讨论尚存的挑战。
• 对该领域超过30个研究工作进行对比性讨论。

实验结果

研究问题

• RQ1 雾计算在智慧城市中可以增值的主要用例场景有哪些？
• RQ2 理想的雾计算平台应支持哪些基本特性和功能以实现智慧城市中可持续的物联网？
• RQ3 在城市环境中部署雾平台面临的未解决挑战和未来研究方向是什么？

主要发现

• 雾计算将数据处理转向边缘/叶节点，以降低带宽、延迟和对中心云的负载。
• 边缘分析实现上下文感知、实时处理，并在云连接间歇时提高可靠性。
• 本综述识别出十个主要的雾特征以及在各用例中的共同特征。
• 相比于超过30个现有研究，雾平台需要具备特定功能以支持可持续的智慧城市感知基础设施。
• 讨论了若干未解决的挑战和未来方向，以指导平台开发与部署。
• 覆盖智慧农业、交通、医疗保健、废物管理、水、温室气体、电网和零售的用例，展示了实际的雾使能架构。