Design and Management of Fog Networks

随着物联网（IoT）的出现，任何设备，无论多小，都能够连接到互联网并监控/控制物理元素，因此智能城市，智能医疗保健和智能交通等应用成为可能。通常，由这些设备生成的数据经由网络基础设施传输到云，以进行处理/存储。然而，由于物联网设备的数据量、分布和规模非常大，在云中处理所有数据是不切实际的。特别是，当涉及到具有严格延迟要求的物联网应用时，云计算无法充分满足这些要求。为了克服这些缺陷，出现了一种新的范例，称为雾计算。这种范例已经被引入作为一种有前途的解决方案，通过将计算（和存储）能力移动到用户附近来支持广泛的物联网应用，从而在物联网-雾-云连续体沿着任何地方处理数据;目标是满足强加的要求（例如，延迟），并减少网络流量的爆炸。 最近，在雾基础设施的资源管理方面做出了显着的贡献。实际上，已经提出了若干模型和方案来管理资源，目的是满足IoT应用的要求（例如，延迟），同时最小化总成本（例如，带宽和能量）。然而，所有这些贡献都假设雾基础设施的存在。在这个项目中，我们将开发新的模型和工具，用于物联网-雾-云连续体中雾基础设施的有效设计/规划。更具体地说，我们将开发一个数学上严格的公式，研究和分析雾设计的动力学和特性。特别是，我们计划开发的混合方法，联合收割机非常有效的元分析，数学规划方法，利用结构的问题，同时减少组合爆炸。然后，我们将进行研究，处理关键的设计问题：设计的可扩展性方面的负载增加和地理扩展随着时间的推移;和鲁棒性的配置方面的故障。然而，即使采用最佳设计，也可能并且将会发生过载和不平衡的利用（例如，当实际负载模式改变和/或超过在设计阶段期间使用的估计/预期负载时）。因此，我们也将开发新的自适应资源管理方案，以满足应用程序的要求，在一个动态/不确定的环境。更具体地说，我们将开发有效的方案，允许调整/重新优化当前支持的应用程序的雾基础设施中的资源配置，以应对这些不可预测的情况;目标是为这些应用程序提供服务质量保证。

With the emergence of Internet of Things (IoT), where any device, however small, is able to connect to the Internet and monitor/control physical elements, several applications were made possible such as smart cities, smart healthcare and smart transportation. Generally, data generated by these devices is transmitted, via the network infrastructure, to the cloud, to be processed/stored. However, with the rate, distribution and scale of extraordinary data from IoT devices, processing all the data in the cloud would be impractical. Particularly, when it comes to IoT applications with stringent delay requirements, cloud computing cannot adequately address these requirements. To overcome these deficiencies, a new paradigm, called fog computing, has emerged. This paradigm has been introduced as a promising solution to support wide range of IoT applications by moving the computing (and storage) power to the proximity of users, and thus processing data anywhere along the IoT-Fog-Cloud continuum; the objective is to meet the imposed requirements (e.g., delay), if any, of IoT applications and reduce the explosion in network traffic. Recently, there has been notable contributions in resource management of the fog infrastructure. Indeed, several models and schemes have been proposed to manage resources, with the objective to satisfy the requirements of IoT applications (e.g. delay) while minimizing the overall cost (e.g., bandwidth and energy). However, all these contributions assume the existence of the fog infrastructure. In this project, we will develop new models and tools for the efficient design/planning of fog infrastructure in the IoT-fog-cloud continuum. More specifically, we will develop a mathematically rigorous formulation, to study and analyze the dynamics and properties of fog design. In particular, we plan to develop hybrid approaches that combine extremely efficient meta-heuristics, with mathematical programming approaches that exploit the structure of the problem while curtailing combinatorial explosion. Then, we will carry out studies dealing with key design issues: the scalability of designs with respect to load increases and geographical expansion over time; and the robustness of configurations with respect to failures. However, even with an optimal design, overload and unbalanced utilization can and will happen (e.g., when actual load patterns change and/or exceed the estimated/expected load used during the design phase). Thus, we will also develop novel adaptive resource management schemes to satisfy application requirements in a dynamic/uncertain environment. More specifically, we will develop efficient schemes that allows to adapt/re-optimize resource provisioning in the fog infrastructure, of currently supported applications, in response to these unpredictable situations; the objective is to provide quality of service assurance to these applications.