Collaborative Service Provisioning at the Edge in 5G Wireless Networks

5G 无线网络边缘的协作服务配置

• 批准号: RGPIN-2019-05667
• 负责人: Hassanein, Hossam
• 金额: $ 6.48万
• 依托单位: Queen's University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2020
• 资助国家: 加拿大
• 起止时间: 2020-01-01 至 2021-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=715700
• 关键词: Collaborative; Service; Provisioning; Edge; 5G

5G, the next generation mobile network, promises to provide ultra-reliable high-speed communications infrastructure to the growing number of mobile users, including connected devices, machines and vehicles associated with the Internet of Things (IoT), as well as the highly demanding steaming video traffic. Services in 5G networks will require support for high mobility, high data rates and low response time. Furthermore, processing an ever-increasing volume of data in real time requires innovative solutions that leverage new developments and networking infrastructures that enable data processing as close to the source as possible. This is known as edge computing. Edge computing has been proven to have a significant impact on offloading traffic/computations from backhaul links/servers and improving users' Quality of Service (QoS). Collaborative edge computing services are provided through the use of the computing, storage and communication resources within user devices, e.g. smart phones, in addition to the infrastructure of the service provider. This proposed research will use edge resources to enhance the ability of 5G networks to meet users' demands and QoS requirements. The research uses novel predictive and collaborative techniques for service provisioning that adapt to changes in user mobility patterns and traffic demands. Machine learning techniques will be used to enhance predictions. The research will be instrumental in achieving ubiquitous wireless broadband access for Canadians and will enhance Canada's position in the telecommunications and mobile services sectors. Training of highly qualified personnel involved in this program will include experience in 5G network design, edge computing techniques and resource representation and management. I expect that five PhD, three Master's and four undergraduate students will receive training through this research program. There is a strong demand for these HQP in the information technology and telecommunications sectors and their future employment will accelerate disseminating next-generation communications technology to Canadian industry.

5G是下一代移动的网络，有望为日益增长的移动的用户提供超可靠的高速通信基础设施，包括与物联网（IoT）相关的连接设备、机器和车辆，以及要求极高的流视频流量。5G网络中的服务将需要支持高移动性、高数据速率和低响应时间。此外，要在真实的时间内处理不断增加的数据量，需要创新的解决方案，这些解决方案应利用新的发展和网络基础设施，使数据处理尽可能接近源。这被称为边缘计算。边缘计算已被证明对从回程链路/服务器卸载流量/计算以及提高用户的服务质量（QoS）具有重大影响。除了服务提供商的基础设施之外，还通过使用用户设备（例如智能电话）内的计算、存储和通信资源来提供协作边缘计算服务。 这项研究将利用边缘资源来增强5G网络满足用户需求和QoS要求的能力。该研究使用新的预测和协作技术来提供服务，以适应用户移动模式和流量需求的变化。机器学习技术将用于增强预测。这项研究将有助于实现加拿大人无处不在的无线宽带接入，并将提高加拿大在电信和移动的服务部门的地位。 参与该计划的高素质人员的培训将包括5G网络设计，边缘计算技术以及资源表示和管理方面的经验。我预计，五个博士，三个硕士和四个本科生将通过这个研究计划接受培训。信息技术和电信部门对这些HQP的需求很大，他们未来的就业将加速向加拿大工业传播下一代通信技术。