CAREER: Towards Realizing Timely Information Transfer and Processing for Networked Communication Systems

职业：实现网络通信系统的及时信息传输和处理

• 批准号: 2146099
• 负责人: Ahmed Arafa
• 金额: $ 50万
• 依托单位: University of North Carolina at Charlotte
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-09-15 至 2027-08-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2146099&HistoricalAwards=false
• 关键词: CAREER; Towards; Realizing; Timely; Information

With the ever-growing amounts of data exchanged in today's world, there needs to be a reliable means for timely information processing and transfer between the end users. Inspired by the novel age-of-information (AoI) metric that assesses information freshness, this proposal offers a pathway towards realizing the ex- change of data in a timely manner in federated learning (FL), cloud computing, and remote sensing systems. It introduces a novel information timeliness metric, AoI, into the study of these systems, and investigates various approaches to achieve timely learning, computing and sensing over networks. It has the potential to become an enabler for various applications, including collaborative autonomous driving, precision health- care, and others. As an integral part of this research proposal, an extensive educational plan that involves K-12, undergraduate and graduate level agendas is proposed.This project spans three fundamental information processing categories. The first involves intelligent agents in a FL setup. Novel agent scheduling and efficient model compression algorithms are proposed for this category to realize the notion of timely FL at-scale. The second considers clients in cloud computing systems, for which innovative job uploading policies are devised under system-level constraints to achieve timely job completions. Finally, the third category focuses on remote sensing, and presents novel variable length coding schemes to enable timely multi-process tracking over noisy communication channels. This project has the potential to transform the way information acquisition and processing systems operate under stringent communication and resource constraints, while the educational plan provides the necessary tools to reason about the timeliness of information in networked systems.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.

随着当今世界交换的数据量不断增加，需要有一种可靠的手段来及时处理和在最终用户之间传输信息。受评估信息新鲜度的新的信息年龄(AOI)度量的启发，该建议提供了一条在联合学习(FL)、云计算和遥感系统中实现数据及时交换的途径。它将一种新的信息时效性度量AOI引入到这些系统的研究中，并研究了在网络上实现及时学习、计算和感知的各种方法。它有可能成为各种应用的推动者，包括协作自动驾驶、精准医疗等。作为这项研究计划的一个组成部分，提出了一个广泛的教育计划，涉及K-12、本科生和研究生的议程。这个项目跨越了三个基本的信息处理类别。第一个涉及FL设置中的智能代理。针对这一类提出了新颖的代理调度和高效的模型压缩算法，以实现规模上的实时FL的概念。第二种考虑云计算系统中的客户，针对这些客户，在系统级约束下设计创新的作业上传策略，以实现作业的及时完成。最后，第三类针对遥感，提出了新的可变长度编码方案，以在噪声通信信道上实现及时的多进程跟踪。该项目有可能改变信息获取和处理系统在严格的通信和资源限制下的运行方式，而教育计划提供了必要的工具来推理网络系统中信息的及时性。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势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

Timely Multi-Process Estimation with Erasures

• DOI: 10.1109/ieeeconf56349.2022.10051950
• 发表时间: 2022-09
• 期刊: 2022 56th Asilomar Conference on Signals, Systems, and Computers
• 作者: Karim Banawan;A. Arafa;Karim G. Seddik

Heirarchical Federated Learning in Delay Sensitive Communication Networks

• DOI: 10.1109/ieeeconf56349.2022.10052096
• 发表时间: 2022-10
• 期刊: 2022 56th Asilomar Conference on Signals, Systems, and Computers
• 作者: Abdulmoneam Ali;A. Arafa