CNS Core:Medium:Systems Challenges in Scaling Distributed Intelligent Applications

CNS 核心：中：扩展分布式智能应用程序的系统挑战

• 批准号: 1901466
• 负责人: Junchen Jiang
• 金额: $ 117.97万
• 依托单位: University of Chicago
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-07-01 至 2025-06-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1901466&HistoricalAwards=false
• 关键词: CNS; Core; Medium; Systems; Challenges

The rapid proliferation of smart edge devices and breakthroughs in machine learning are poised to change how applications extract insights from sensor data, creating a new class of Distributed Intelligent Applications (DIAs) that include video monitoring, autonomous device control, and response for network cybersecurity. The project explores new analysis, distribution, and resource management approaches that enable DIAs to employ geographically distributed architectures, spreading analytics across sensors, edge clusters, and cloud datacenters. This approach is a major shift from today's approach that collocates data and analytics in the cloud.Distributed Intelligent Applications (DIAs) present fundamental challenges arising from distribution, bursts and high computational demands, as well as complex analytics. First, the project will explore systematic approaches that distribute DIA analysis across sensor, edge, and cloud resources to reduce cost and increase application quality. Second, the project blends analytics and communication, enabling new options to optimize capability and cost. Third, to meet realtime and bursty resource requirements, the project will explore new resource management approaches for shared, open resource environments that provide essential application guarantees.The proposed research will create capabilities that will increase the number and the capability of DIAs, allowing such applications greater accuracy, timeliness, and efficiency at lower cost. The project will involve a number of undergraduate and graduate students, exposing them to real edge computing testbeds, experimental studies, and exciting applications. These opportunities and impacts will include course enrichment and undergraduate research opportunities. The project team will bring novel insights and energy to several large outreach programs to broaden participation in computing.The project will release data and source code generated by the project. Such software artifacts will be open sourced via github (https://github.com/) or departmental storage service, for the project period. After the project's end, the team will provide best-effort support, helping others to use the project results as expertise and team effort is available. As opportunity arises, we will work with industry partners to make results and insights even more broadly available.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.

智能边缘设备的快速普及和机器学习的突破将改变应用程序从传感器数据中提取洞察力的方式，创建一类新的分布式智能应用程序（DIA），包括视频监控，自主设备控制和网络网络安全响应。该项目探索了新的分析、分发和资源管理方法，使DIA能够采用地理上分布式的架构，在传感器、边缘集群和云计算中心之间传播分析。分布式智能应用（DIA）面临着分布、突发和高计算需求以及复杂分析等根本性挑战。首先，该项目将探索跨传感器、边缘和云资源分布DIA分析的系统方法，以降低成本并提高应用质量。其次，该项目融合了分析和沟通，使新的选择，以优化能力和成本。第三，为了满足实时和突发性的资源需求，该项目将探索新的资源管理方法，用于共享的开放资源环境，提供必要的应用保证。拟议的研究将创建能力，以增加DIA的数量和能力，使这些应用以更低的成本获得更高的准确性，及时性和效率。该项目将涉及一些本科生和研究生，让他们接触到真实的边缘计算测试平台、实验研究和令人兴奋的应用。这些机会和影响将包括课程丰富和本科生的研究机会。该项目团队将为几个大型推广计划带来新的见解和能量，以扩大对计算的参与。该项目将发布项目生成的数据和源代码。在项目期间，这些软件工件将通过github（https：//github.com/）或部门存储服务开源。项目结束后，团队将提供最大努力的支持，帮助其他人使用项目成果作为专业知识和团队努力。随着机会的出现，我们将与行业合作伙伴合作，使成果和见解更广泛地提供。该奖项反映了NSF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

Scheduling Challenges for Variable Capacity Resources

可变容量资源的调度挑战

• 发表时间: 2021
• 期刊: Proceedings of JSSPP21
• 作者: Zhang, Chaojie;Chien, Andrew A.
• 通讯作者: Chien, Andrew A.

Spatula: Efficient cross-camera video analytics on large camera networks

• DOI: 10.1109/sec50012.2020.00016
• 发表时间: 2020-08
• 期刊: 2020 IEEE/ACM Symposium on Edge Computing (SEC)
• 作者: Samvit Jain;Xun Zhang;Yuhao Zhou;Ganesh Ananthanarayanan;Junchen Jiang;Yuanchao Shu;P. Bahl;Joseph Gonzalez

Adapting Datacenter Capacity for Greener Datacenters and Grid

• DOI: 10.1145/3575813.3595197
• 发表时间: 2023-01
• 期刊: Proceedings of the 14th ACM International Conference on Future Energy Systems
• 作者: Liuzixuan Lin;A. Chien

A Foundation for Real-time Applications onFunction-as-a-Service

功能即服务实时应用程序的基础

• 发表时间: 2024
• 期刊: A Foundation for Real-time Applications onFunction-as-a-Service
• 作者: Nguyen, Hai Duc;Chien, Andrew A.
• 通讯作者: Chien, Andrew A.

Privid: Practical, Privacy-Preserving Queries on Public Video

Privid：公共视频的实用、隐私保护查询

• 发表时间: 2022
• 期刊: 19th USENIX Symposium on Networked Systems Design and Implementation
• 作者: Cangialosi, Frank;Agarwal, Neil;Arun, Venkat;Jiang, Junchen;Narayana, Srinivas;Sarwate, Anand;Netravali, Ravi
• 通讯作者: Netravali, Ravi