Enabling Technologies for hyper-connected, data driven, and service oriented networks of the future

未来超连接、数据驱动和面向服务的网络的支持技术

• 批准号: RGPIN-2019-05477
• 负责人: Assi, Chadi
• 金额: $ 2.84万
• 依托单位: Concordia University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2022
• 资助国家: 加拿大
• 起止时间: 2022-01-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=750637
• 关键词: Enabling; Technologies; hyper; connected; data

Advancements in technology and communication in the recent decades have always been on a constant rise, culminating into new models such as the LTE standard for 4G networks for provisioning high data rates responding to the high bandwidth needs of modern mobile applications, and the mobile cloud computing paradigm for leveraging the computing and storage power of data centers to address the computation and energy limitations of mobile devices. However, today, with the cities needing to contain the ever increasing surge in population, and technology needing to keep up with the unparalleled advancement in cutting edge services of the smart city vision, a recent research wave have been pushing for a dramatic evolution of the existing networking infrastructure and communication models, aiming to address the newly imposed smart city service requirements. Future services have heterogeneous stringent requirements, from ultra low latency and reliability, e.g. self-driving, remote surgeries, to very high bandwidth and data rates e.g. advanced gaming, VR, AR, and often require high mobility. 5G (and beyond) technologies promise to achieve this vision, e.g. a) address the high data rates requirement by densifying the cells with MIMO, improving the radio spectrum efficiency and extending it to include higher frequencies. b) address the expansion of IoT devices and huge data consumption by densifying the network and introducing UAV communication. c) address the ultra low latency communication and the tactile internet by pushing the cloud resources close to the end users and enabling various radio access technologies and hence the concepts of fog computing and multi-access edge computing, which is part of a paradigm shift from centralized to distributed services. d) address the dynamic and uncertain nature of traffic flows by softwarizing the network and its functions with the concepts of SDN and NFV, and hence facilitating traffic mobility and migration. e) address the heterogeneity of the services by allocating virtual networks with the concept of network slicing. Nevertheless, realizing the future networks still requires addressing numerous challenges. How to guarantee ultra low latency in dense areas with limited edge resources. How to minimize infrastructure costs when realizing the new communication models. How to address energy limitation for IoT and other communicating devices. How to ensure reliability of UAVs and other serving stations while maintaining low resource costs. How to efficiently manage interference resulting from the communication with the densified stations and UAVs. How to efficiently allocate spectrum and computation resources for maximizing resource utilization. How to efficiently cache data on the edge and UAVs. How to account for security threats in spite of the new architectures and communication models. Those and many other problems still need to be treated for fully realizing the future envisioned networks.

近几十年来，技术和沟通方面的进步一直在不断上升，最终导致了新模型，例如4G网络的LTE标准，用于为现代移动应用程序提供高数据速率的高度带宽需求以及移动云计算范式的高带宽需求，以及利用数据中心的计算和存储功能来解决计算和能源限制的数据中心的计算和存储功能。但是，如今，由于城市需要遏制人口的不断增长，并且需要跟上智能城市视觉的最前沿服务的无与伦比的进步，因此最近的研究浪潮一直在推动现有的网络基础架构和通信模型的巨大演变，旨在满足新实现的新型智能城市服务的需求。未来的服务从超低潜伏期和可靠性（例如自动驾驶，远程手术，到很高的带宽和数据速率，例如高级游戏，VR，AR，通常需要高机动性。 5G（及以后）技术有望实现这一愿景，例如a）通过用MIMO致密细胞，提高无线电频谱效率并将其扩展到包括较高频率来满足高数据速率的需求。 b）通过致密网络并引入无人机通信来解决物联网设备和大量数据消耗的扩展。 c）通过将云资源推向最终用户，并启用各种无线电访问技术，从而解决超低的潜伏通信和触觉互联网，从而解决了雾计算和多访问边缘计算的概念，这是范式从集中式转移到分布式服务的范式转移的一部分。 d）通过通过SDN和NFV的概念软化网络及其功能来解决流量流的动态和不确定性质，从而促进了交通流动性和迁移。 e）通过用网络切片的概念分配虚拟网络来解决服务的异质性。然而，意识到未来的网络仍然需要解决众多挑战。如何保证边缘资源有限的密集区域中的超低潜伏期。在实现新的通信模型时，如何最小化基础架构成本。如何解决物联网和其他通信设备的能源限制。如何确保无人机和其他服务站的可靠性，同时保持低资源成本。如何有效管理与致密电台和无人机的通信产生的干扰。如何有效分配频谱和计算资源，以最大程度地利用资源利用。如何在边缘和无人机上有效地缓存数据。尽管有新的体系结构和通信模型，但如何考虑安全威胁。这些和许多其他问题仍然需要得到充分实现未来设想的网络的处理。