Software defined networking-enabled beyond 5G network slicing for smart cities applications

该项目的总体目标是开发端到端(E2E)Beyond 5G网络切片框架，以支持应急响应、智能建筑和视频监控三个智慧城市应用。网络切片是部署在共享物理基础设施上的E2E逻辑网络。每个网络片配置有提供特定服务所需的一组网络资源(即，网络、计算、内存和存储资源)及其映射到服务性能要求的服务级别协议。如何在保持片隔离的同时为片动态分配网络资源是一个难题。此外，切片分配也是一个具有挑战性的问题，因为共享资源可能会阻塞带宽，导致网络分配效率低下和应用程序性能不佳。本项目的另一个目标是提出新的高效的片内和片间资源分配算法，并通过数学和仿真技术评估其性能。最后，我们将对所提出的网络切片框架和切片资源分配算法进行概念验证。研究的预期成果是提出了E2E Beyond 5G网络切片框架和网络切片资源分配算法。交付成果是用于创建、部署和协调Beyond 5G网络切片的软件，展示了框架在支持选定的三个智能城市应用方面的有效性，以及演示了拟议的网络切片资源分配算法的可实现性能。该项目将节省与智慧城市运营相关的成本，并将为加拿大电信服务提供商提供竞争优势。该项目将培训具有高需求技能的HQP。

The overall goal of this project is to develop an end-to-end (E2E) beyond 5G network slicing framework for support of three smart cities applications, namely, emergency response, smart building, and video surveillance. A network slice is an E2E logical network deployed over a shared physical infrastructure. Each network slice is configured with a set of network resources (i.e., networking, computing, memory and storage resources) needed to deliver a specific service with its service level agreement which maps to the service performance requirements. How to dynamically allocate network resources to a slice while maintaining slice isolation is a difficult problem. Further, slice allocation is also a challenging problem because shared resources could block bandwidth leading to inefficient network allocation and sub-optimal application performance. Another objective of this project is to propose new and efficient algorithms for intra-slice and inter-slice resource allocation, and evaluate their performance through mathematical and simulation techniques. Finally, we shall perform proof of concept implementation of the proposed network slicing framework and slice resource allocation algorithms. The anticipated outcomes of the research are the proposed E2E beyond 5G network slicing framework and network slice resource allocation algorithms. The deliverables are a software for creating, deploying, and orchestrating beyond 5G network slices, a demonstration of framework's effectiveness in supporting the three selected smart cities applications, and a demonstration of the achievable performance of the proposed network slice resource allocation algorithms. The project will provide cost savings related to smart city operation and will offer competitive advantage to Canadian telecom service providers. The project will train HQP with highly in-demand skills.