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.

随着当今世界上不断增长的数据交换，需要有一种可靠的手段来及时的信息处理和最终用户之间的传输。受到评估信息新鲜度的新信息（AOI）度量的启发，该提案为及时实现数据的途径在联合学习（FL），云计算和遥感系统中及时实现数据提供了途径。它将新颖的信息及时度量aoi引入了这些系统的研究，并研究了各种方法以实现网络上的及时学习，计算和感知。它有可能成为各种应用程序的推动者，包括协作自主驾驶，精密卫生保健等。作为本研究建议不可或缺的一部分，提出了一项广泛的教育计划，涉及K-12，本科和研究生级别的议程。该项目涵盖了三个基本信息处理类别。第一个涉及FL设置中的智能代理。为此，提出了新型的代理调度和有效的模型压缩算法，以实现及时的FL尺度概念。第二个考虑了云计算系统中的客户，为此，创新的作业上传政策是在系统级别的约束下设计的，以实现及时的工作完成。最后，第三类着重于遥感，并介绍了新颖的可变长度编码方案，以使噪声通信渠道及时进行多进程跟踪。该项目有可能改变信息获取和处理系统在严格的沟通和资源限制下运行的方式，而教育计划则提供了必要的工具来推理网络系统中信息及时性的必要工具。该奖项反映了NSF的法定任务，并且已经是认为值得通过基金会的智力优点和更广泛影响的评论标准来评估值得支持。

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