CNS Core: Small: Sensor-based Wireless Network Management via Edge Computing

CNS 核心：小型：通过边缘计算进行基于传感器的无线网络管理

• 批准号: 1908910
• 负责人: Eric Rozner
• 金额: $ 30万
• 依托单位: University of Colorado at Boulder
• 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: 2019-10-01 至 2024-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1908910&HistoricalAwards=false
• 关键词: CNS; Core; Small; Sensor; based

As Internet-of-Things, mobile health, autonomous vehicles, cyber-physical systems, virtual reality, and smart environments proliferate, wireless spectrum demand continues to grow at a significant rate. This proposal investigates new ways of managing wireless networks through the advanced integration of emerging trends in software-driven networking, ubiquitous computing deployments, and sensor-driven analysis. The proposal supports the National Science Foundation's mission to advance prosperity by enabling wireless industries to more efficiently and flexibly control their networks. The investigator will work closely with the wireless communication industry that contributes $475 billion annually to America's economy each year and supports up to 4.7 million jobs nationally. The project further benefits society by developing sensor-based computing educational modules that will be released on TeachEngineering, a free searchable engineering curricula library for K-12 educators.Two major thrusts will be studied to build an architecture that enables practical sensor-based wireless network management. The first thrust aims to utilize sensor data to more effectively and flexibly manage the wireless network. First, objects in the sensory domain will be aligned with objects in the wireless domain through behavior analysis techniques in both domains. Second, techniques will be designed to flexibly schedule network traffic based on the actions of mobile device users. Third, a programmable framework and corresponding feasibility tools allow administrators to configure this new type of network architecture. A second major thrust in this proposal makes analyzing sensory data at the network edge more efficient. First, user and traffic context are used to determine how much edge resources should be allocated for sensor analysis. Second, computational demands on network edge resources are lessened via context-aware sampling rate algorithms. In addition, new techniques utilize wireless information to lessen sensor-based processing. The research results will be incorporated into courses at the University of Colorado Boulder, scientific publications, and released as open-source software.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.

随着物联网、移动医疗、自动驾驶汽车、网络物理系统、虚拟现实和智能环境的激增，无线频谱需求继续以显着的速度增长。本提案通过软件驱动网络、无处不在的计算部署和传感器驱动分析等新兴趋势的高级集成，研究了管理无线网络的新方法。该提案支持美国国家科学基金会的使命，即通过使无线行业能够更有效、更灵活地控制其网络来促进繁荣。无线通信行业每年为美国经济贡献4750亿美元，并为全国提供470万个就业岗位，调查人员将与该行业密切合作。该项目通过开发基于传感器的计算教育模块进一步造福社会，这些模块将在TeachEngineering上发布，TeachEngineering是一个面向K-12教育工作者的免费可搜索工程课程图书馆。将研究两个主要的重点，以建立一个架构，使实用的基于传感器的无线网络管理。第一个目标是利用传感器数据更有效、更灵活地管理无线网络。首先，通过在两个领域的行为分析技术，将感官领域的物体与无线领域的物体对齐。其次，根据移动设备用户的行为，设计灵活调度网络流量的技术。第三，可编程框架和相应的可行性工具允许管理员配置这种新型网络架构。该提案的第二个主要推动力是在网络边缘更有效地分析感官数据。首先，使用用户和交通环境来确定应该分配多少边缘资源用于传感器分析。其次，通过上下文感知采样率算法减少了对网络边缘资源的计算需求。此外，新技术利用无线信息来减少基于传感器的处理。研究结果将被纳入科罗拉多大学博尔德分校的课程和科学出版物中，并作为开源软件发布。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

Poster: Rethinking Wireless Network Management Through Sensor-driven Contextual Analysis

海报：通过传感器驱动的情境分析重新思考无线网络管理

• 发表时间: 2020
• 期刊: HotMobile '20: Proceedings of the 21st International Workshop on Mobile Computing Systems and Applications
• 作者: Irshad, Shazal;Rozner, Eric;Bhartia, Apurv;Chen, Bo
• 通讯作者: Chen, Bo

You Can't See Me: Providing Privacy in Vision Pipelines via Wi-Fi Localization

• DOI: 10.1109/lanman58293.2023.10189418
• 发表时间: 2023-07
• 期刊: 2023 IEEE 29th International Symposium on Local and Metropolitan Area Networks (LANMAN)
• 作者: Shazal Irshad;Ria Thakkar;Eric Rozner;Eric Wustrow

Sequoia: enabling quality-of-service in serverless computing

• DOI: 10.1145/3419111.3421306
• 发表时间: 2020-10
• 期刊: Proceedings of the 11th ACM Symposium on Cloud Computing
• 作者: Ali Tariq;Austin Pahl;Sharat Nimmagadda;Eric Rozner;Siddharth Lanka

Poster: DeepFind: Sensor-driven Inference Acceleration for Continuous Deep Mobile Vision Applications

海报：DeepFind：用于连续深度移动视觉应用的传感器驱动推理加速

• 发表时间: 2020
• 期刊: HotMobile '20: Proceedings of the 21st International Workshop on Mobile Computing Systems and Applications
• 作者: Yoo, Chungkuk;Sarmin, Saiyma;Hwang, Inseok;Rozner, Eric;Cho, Minsik
• 通讯作者: Cho, Minsik

A Picture is Worth 1,000 Millimeters: Combining Vision and Wi-Fi to Improve Localization

• DOI: 10.1109/wowmom57956.2023.00020
• 发表时间: 2023-06
• 期刊: 2023 IEEE 24th International Symposium on a World of Wireless, Mobile and Multimedia Networks (WoWMoM)
• 作者: Shazal Irshad;Eric Rozner;Apurv Bhartia;Bo Chen