Dynamic Resource Allocation and Pricing for Fog-Cloud Networking as a Service

雾计算（包括边缘计算）概念正在获得巨大的动力，因为它们可以提供低服务延迟，结合地理上的分布式计算，独立于用户位置。这些成分可以显著增强触觉互联网、物联网和多用户应用的能力。为了实现这些目标，需要一个发达且经济可行的雾云计算基础设施。在本建议中，我们讨论了与这一目标有关的一些重要问题。特别是，我们认为应用程序应该能够访问多节点和多层雾云计算资源，实现分布式计算，其中网络方面非常重要。考虑的计算节点可以属于不同的所有者，可以包括边缘节点、本地数据中心和远程数据中心。对于用户和应用程序来说，在这样一组分布式计算和网络资源中管理资源分配可能过于复杂。为了解决这个问题，我们提出了一种服务，我们将其命名为雾云网络即服务（FCNaaS），其中FCNaaS运营商（FCNO）结合了覆盖网络和代理的角色。覆盖网络部分管理给定需求的网络和计算资源分配，而代理部分促进用户、应用程序和网络计算资源所有者之间的长时间交互，涉及FCNO的资源预留和定价。

The Fog computing (comprising the Edge computing) concepts are gaining a significant momentum since they can provide low service latency combined with geographically distributed computing, independent of the user locations. These ingredients can significantly empower Tactile Internet, IoT and multi-user applications. To achieve these objectives, a well-developed and economically viable infrastructure for the Fog-Cloud computing is needed. In this proposal, we address some important issues related to this goal. In particular, we believe that the applications should have access to multi-node and multi-layer Fog-Cloud computation resources, enabling distributed computations, where the networking aspect is of great importance. The considered computation nodes can belong to different owners and can include edge nodes, local data centers, and distant data centers. Managing resource allocation in such a distributed set of computing and networking resources can be too complicated for users and applications. To address this issue we propose a service that we name Fog-Cloud Networking as a Service (FCNaaS) where the FCNaaS operator (FCNO) combines the role of an overlay network and a broker. The overlay network part manages the networking and computing resource allocation to a given demand while the broker part facilitates long-time-scale interaction between the users, applications and networking-computing resource owners that involves resource reservations for FCNO and pricing. The research will be focused on three areas related to FCNaaS: 1) Resource management architecture for Fog-Cloud Networking, 2) Dynamic resource allocation and related economic framework, and 3) Pricing and resource reservations. In particular, we will develop AI based resource allocation models within an economic framework that takes into account heterogeneous environment with several resource and application providers. Also, using a game theoretical framework we will develop models for pricing that give incentives to each player to participate in the market in an economically efficient and balanced way that provides benefits to all players. The research results will be useful to Canadian application providers, network operators, and computing node owners for optimizing their operations and to grow their market shares. The developed knowledge and models will be also useful to the government regulatory bodies for providing social wellness of the offered services. Also, the training of HQP is an integral part of the proposed research program and the students will acquire important skills in the domain that is becoming of high importance to several Canadian industries.