SBIR Phase I: 5G Network Performance and Demand Prediction for Smart Cities

SBIR 第一阶段：智慧城市的 5G 网络性能和需求预测

• 批准号: 1914127
• 负责人: Payman Samadi
• 金额: $ 22.5万
• 依托单位: EINO, INC.
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-07-01 至 2020-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1914127&HistoricalAwards=false
• 关键词: SBIR; Phase; 5G; Network; Performance

The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project will result from enabling self-evolving telecommunication networks to ensure that reliable and high-speed internet access is available in large metropolitan areas and mission critical applications in smart cities will receive guaranteed Quality of Service, while the capital and operational costs of the networks are reduced. Furthermore, this technology will reduce the energy consumption of telecommunication networks by moving resources where and when they are needed, avoiding over-provisioning and waste in idle resources.This Small Business Innovation Research (SBIR) Phase I project develops a first of its kind novel Artificial Intelligent-based network performance and demand prediction platform to guarantee 5G connectivity in metropolitan areas and eventually in smart cities. With 68% of the world population living in urban areas by 2050, constant movement of people and diversity in 5G applications network requirements, network optimization is critical. However, achieving optimal network configuration requires accurate prediction of future network demand. The proposed research will utilize the external contextual data of mass human movement and their activity along with a portfolio of machine learning methodologies to perform accurate network demand prediction and consequently optimal resource allocation. The main objective of this project is to develop and deploy an automated cloud-based software that performs prediction on network key performance indicators in urban areas up to seven days in advance. This software solution enables network operators to identify and anticipate accurate temporal and spatial demands and anomalies, understand the factors that will cause demand variations, and pinpoint future opportunities for optimization based on this information.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

这项小型企业创新研究（SBIR）I阶段项目的更广泛的影响/商业潜力将是由实现自我不断发展的电信网络而造成的，以确保在较大的大都市地区可靠地提供可靠和高速的互联网访问，并且智能城市中的任务关键应用程序将获得保证的服务质量，而网络的资本和运营成本却降低了。此外，这项技术将通过将资源转移到需要的位置和何时何时以及浪费闲置资源中的资源来减少电信网络的能源消耗。本小型企业创新研究（SBIR）I阶段项目开发了这种基于人工智能的网络性能和需求预测平台的第一个小型新颖的网络预测平台，以保证Metropolitanan和SmartCorpopolitan的5G连接性。到2050年，有68％的世界人口居住在城市地区，人们在5G应用网络需求中的不断运动和多样性的发展至关重要。但是，实现最佳网络配置需要准确预测未来的网络需求。拟议的研究将利用大众运动及其活动的外部上下文数据以及机器学习方法组合来执行准确的网络需求预测，从而进行最佳资源分配。该项目的主要目的是开发和部署一个基于云的自动化软件，该软件对城市地区的网络关键绩效指标进行预测长达7天。该软件解决方案使网络运营商能够识别和预测准确的时间和空间需求和异常，了解会导致需求变化的因素，并根据此信息来确定未来的优化机会。该奖项反映了NSF的法定任务，并通过该基金会的智力功能和广泛的影响来评估NSF的法定任务。