Planning, Design, and Management of Fog/IoT Environments

随着物联网(IoT)、普适计算、医疗保健服务、传感器网络和移动设备的日益普及，网络边缘产生了大量数据。目前，云是存储、处理和管理这些数据的最可行的解决方案。然而，云通常位于很远的地方，这意味着它们对于对时间敏感的服务来说效率不高。此外，将海量数据从边缘移动到云会导致更高的带宽消耗。由于云数据中心可能分布在多个国家，移动数据可能会引发监管、安全和隐私问题。为此，引入了雾计算(又称边缘计算)的概念。雾可以被视为位于底层节点附近的云的延伸，从而为需要它的应用程序提供快速响应。雾节点还可以对数据进行预处理和过滤，以减少所需的带宽。最后，可以将调整后的数据发送到云中进行进一步分析和增强服务配置。到目前为止，雾计算和物联网被认为是未来5G移动网络的关键使能技术。因此，正确规划、设计和管理雾计算环境对于网络提供商将其成本(包括资本和运营成本)降至最低以及用户享受良好体验至关重要。该研究计划的主要目标是开发模型、算法和软件工具来规划、设计和管理雾网络。更准确地说，我们首先要评估与云结合使用的雾计算概念与独立云相比如何提高性能。然后，我们将研究提供商如何在处理成本、延迟、存储、计算等各种考虑因素的同时部署和管理其FOG体系结构。将开发不同的模型、算法和软件工具，以帮助网络运营商和服务提供商在其网络的规划、部署和管理阶段。开发的模型和算法将基于各种优化技术以及机器学习，以实现高效的自主计划、管理和协调。这项研究的成果有望为开发新的算法和工具来规划、设计和管理雾化网络做出重大贡献。它将对所有希望部署和/或管理雾化网络的网络提供商产生重大的经济影响。在技术影响方面，雾网络的适当部署和管理将允许从不同的垂直领域创建新的实时应用和服务。最后，该研究项目也是学生获得物联网和雾计算领域专业知识的绝佳机会，这两个领域在工业界和学术界获得了显著的势头。

With the increasing popularity of the Internet of Things (IoT), pervasive computing, healthcare services, sensor networks, and mobile devices, a lot of data is being generated at the edge of the network. Currently, the cloud is the most viable solution for storing, processing, and managing this data. However, clouds are usually located far away meaning that they are not efficient for time-sensitive services. Furthermore, moving the huge volume of data from edge to cloud leads to higher bandwidth consumption. Since cloud data centers might be located across countries, moving data will likely raise regulatory, security, and privacy issues. For this reason, the concept of fog computing (also known as edge computing) has been introduced. The fog can be seen as an extension of the cloud lying within the proximity of the underlying nodes and therefore providing quick response to applications that require it. Fog nodes can also preprocess and filter data to reduce the required bandwidth. Finally, trimmed data can be sent to the cloud for further analysis and enhanced service provisioning. To date, fog computing and IoT are considered as key enabling technologies for future 5G mobile networks. As a result, proper planning, design, and management of fog computing environments is crucial for network providers to minimize their costs (both capital and operational) and for users to enjoy a good quality of experience. The main goal of this research program is to develop models, algorithms and software tools to plan, design, and manage fog networks. More precisely, we first want to evaluate how the concept of fog computing used in conjunction with the cloud can improve performance compared to a standalone cloud. Then, we will look at how providers can deploy and manage their fog architecture while dealing with various considerations such as cost, delay, storage, compute, etc. Different models, algorithms, and software tools will be developed to assist network operators and service providers in the planning, deployment and management phases of their networks. The developed models and algorithms will be based on various optimization techniques as well as machine learning for efficient autonomous planning, management, and orchestration. The outcome of this research is expected to make significant contributions in developing new algorithms and tools to plan, design and manage fog networks. It will have a significant economic impact for all network providers looking to deploy and/or manage a fog network. In terms of technological impact, a proper deployment and management of fog networks will allow the creation of new real-time applications and services from different verticals. Finally, this research program is also an excellent opportunity for students to acquire expertise in the fields of IoT and fog computing which are gaining significant momentum in industry and academia.