CSR: Small: Collaborative Research: Dispersed Real-time Data Analytics
CSR: Small: Collaborative Research: Dispersed Real-time Data Analytics
批准号:
1717834
负责人:
Abhishek Chandra
金额:
$25.8万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2017
资助国家:
美国
项目状态:
已结题
起止时间:
2017-09-01 至 2022-08-31
中文摘要
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英文摘要
Recent years have seen an explosion of data produced by a wide variety of mobile applications, sensors, and Internet of Things (IoT) devices spread across multiple geographic locations. This data must be aggregated and analyzed to gain real-time insights across several domains. There has also been a dramatic increase in the heterogeneity of the computing platform: compute and storage resources are available at end-user devices and data centers at the edge of the Internet, as well as at centralized clouds. This project proposes algorithms and architectures for leveraging such a dispersed computing platform to perform real-time processing of large volumes of data. Gaining real-time insights from large volumes of data is at the crux of the digital economy, as information from users and sensors must be processed quickly to gain immediate actionable insights. This project aims to make such insights feasible leading to greater productivity and user satisfaction. Data science and analytics is a key area of workforce demand in the US. The proposed educational and outreach activities include new course material and Research Experiences for Undergraduates (REU) programs targeted to provide greater exposure in this area. This project also includes strong outreach initiatives to attract both women and under-represented minorities to data analytics research.This project proposes a two-level architecture for a dispersed real-time analytics system across a large number of autonomous resource providers (ARPs): a global subsystem that allocates resources end-to-end across multiple resource providers, and a local subsystem that schedules resources within each ARP. The global resource allocation process introduces the notion of an aggregation tree that is used for discovering, allocating, and coordinating resources across multiple ARPs. The local resource allocation process orchestrates the movement of computation and data within an ARP. Across both levels, techniques for dealing with dynamic variability in resources and resilience to failure are investigated. All software developed as a result of this project will be clearly documented and open-sourced. For any datasets collected from public sources, sufficient meta-data will be published to enable others to reuse the data for their own purposes. The technical reports and papers produced by the project will be published and shared with the general public. The information generated by the project will be maintained, preserved, and made available for the duration required by NSF. A comprehensive website will provide access to this information. The website URL is: http://geo-anal.cs.umn.edu.
期刊论文(8)
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Towards WAN-aware join sampling over geo-distributed data
针对地理分布式数据进行广域网感知连接采样
DOI:
10.1145/3517206.3526268
发表时间:
2022
期刊:
Analytics and Networking
影响因子:
--
作者:
[Kumar, Dhruv, Wolfrath, Joel, Chandra, Abhishek, Sitaraman, Ramesh K.]
通讯作者:
Sitaraman, Ramesh K.
AggNet: Cost-Aware Aggregation Networks for Geo-distributed Streaming Analytics
AggNet:用于地理分布式流分析的成本感知聚合网络
DOI:
10.1145/3453142.3491276
发表时间:
2021
期刊:
IEEE/ACM Symposium on Edge Computing (SEC
影响因子:
--
作者:
[Dhruv Kumar, Sohaib Ahmad, Abhishek Chandra, Ramesh K. Sitaraman]
通讯作者:
Ramesh K. Sitaraman
DOI:
10.1145/3423211.3425668
发表时间:
2020-12
期刊:
Proceedings of the 21st International Middleware Conference
影响因子:
--
作者:
[A. Jonathan;A. Chandra;J. Weissman]
通讯作者:
A. Jonathan;A. Chandra;J. Weissman
DOI:
10.1145/3431379.3460643
发表时间:
2020-06
期刊:
Proceedings of the 30th International Symposium on High-Performance Parallel and Distributed Computing
影响因子:
--
作者:
[Rankyung Hong;A. Chandra]
通讯作者:
Rankyung Hong;A. Chandra
DOI:
10.1109/ipdps53621.2022.00100
发表时间:
2022-05
期刊:
2022 IEEE International Parallel and Distributed Processing Symposium (IPDPS)
影响因子:
--
作者:
[Joel Wolfrath;N. Sreekumar;Dhruv Kumar;Yuanli Wang;A. Chandra]
通讯作者:
Joel Wolfrath;N. Sreekumar;Dhruv Kumar;Yuanli Wang;A. Chandra
共 7 条
CSR: Small: Location, location, location (L3): Support for Geo-Centric Applications
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财政年份:2007
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负责人:Abhishek Chandra
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依托单位:
国内基金
海外基金
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