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SCC: Integrating Heterogeneous Wide-Area Networks and Advanced Data Science to Bridge the Digital Divide in Rural Emergency Preparedness and Response

SCC：集成异构广域网和先进数据科学，弥合农村应急准备和响应中的数字鸿沟

基本信息

批准号：
1831547
负责人：
Mariya Zheleva
金额：
$ 149.48万
依托单位：
SUNY at Albany
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2018
资助国家：
美国
起止时间：
2018-09-15 至 2024-08-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1831547&HistoricalAwards=false
关键词：
SCC Integrating Heterogeneous Wide Area

项目摘要

This Smart and Connected Communities (SCC) project will conduct innovative research in network architectures and protocols to allow emergency responders in rural areas to use TV white space, WiFi and pocket-switching for communications in areas where mobile broadband are scarce to non-existent. With this new knowledge, this project can develop and implement a framework for information exchange for emergency responders in rural communities. This scientific research contribution thus supports NSF's mission to promote the progress of science and to advance our national welfare with benefits that contribute to the safety and social and economic revitalization of rural communities. Generalizability of results is expected in relation to other rural contexts and policy domains (e.g., law enforcement and health). Research components and key results will be incorporated in existing and new undergraduate and graduate courses, demonstrating the positive impact of interdisciplinary research and promoting the core disciplines to diverse groups of students.The goal of this project is to develop, implement, and systematically analyze a comprehensive framework and a multi-layer platform for timely information collection, integration, exchange and dissemination to support EPR in rural communities. This goal will be met through three primary activities. First, the project will develop a heterogeneous network architecture and corresponding protocols that leverage wide-area wireless backhaul over TV white spaces, WiFi and pocket-switching to provide (i) continuous communication to first responders and (ii) delay-tolerant information access to residents. In addition, the project will design a smartphone app which will support the collection of information from different sources and its exchange among first responders, government agencies and residents. Second, the mobility patterns and network availability collected will enable the development of a dynamic probabilistic community network model. Novel graph-theoretic algorithms will identify information-depleted sub-communities and inform optimal information dissemination strategies. Finally, the project will assess adoption and use of the technologies by various community members to maximize the benefits associated with timely, rich and high-quality information, disseminated through technological devices. Continuous community engagement activities for data provisioning, app design, impact co-evaluation and path to sustainability of the project are key factors for success. The framework will be co-designed and piloted in collaboration with the Town of Thurman, NY. Transferability to the broader rural context will be assessed by engaging two additional rural communities in coordination with Microsoft's Airband initiative.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.

这个智能和互联社区（SCC）项目将对网络架构和协议进行创新研究，使农村地区的应急响应人员能够在移动宽带稀缺或不存在的地区使用电视空白空间、WiFi和口袋交换进行通信。有了这些新知识，该项目可以为农村社区应急人员制定和实施信息交流框架。因此，这项科学研究贡献支持了NSF的使命，即促进科学进步，促进我们的国家福利，为农村社区的安全、社会和经济振兴做出贡献。预期结果可推广到其他农村情况和政策领域（例如，执法和保健）。研究内容和主要成果将纳入现有和新的本科和研究生课程，展示跨学科研究的积极影响，并向不同群体的学生推广核心学科。该项目的目标是制定、实施和系统分析一个全面的框架和多层平台，以便及时收集、整合、交流和传播信息，以支持农村社区的EPR工作。这一目标将通过三项主要活动来实现。首先，该项目将开发一个异构网络架构和相应的协议，利用电视空白空间、WiFi和口袋交换的广域无线回程，提供(i)向第一响应者提供连续通信，（ii）向居民提供容错信息访问。此外，该项目将设计一个智能手机应用程序，该应用程序将支持从不同来源收集信息，并在急救人员、政府机构和居民之间进行交换。其次，收集的移动模式和网络可用性将使动态概率社区网络模型的开发成为可能。新的图论算法将识别信息枯竭的子社区，并告知最佳的信息传播策略。最后，该项目将评估各社区成员对这些技术的采用和使用情况，以便最大限度地利用通过技术设备传播的及时、丰富和高质量的信息。持续的社区参与活动，如数据提供、应用程序设计、影响共同评估和项目的可持续性是成功的关键因素。该框架将与纽约瑟曼镇合作共同设计和试点。微软将与另外两个农村社区合作，配合Airband计划，评估其在更广泛农村环境下的可转移性。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

期刊论文数量（10）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Cross-Boundary Information Sharing Flows in Emergency Management:: Proposing a Conceptual Framework

应急管理中的跨境信息共享流程：提出概念框架

DOI：
10.1145/3543434.3543481
发表时间：
2022
期刊：
DG.O 2022
影响因子：
0
作者：
Chen, Tzuhao;Gil-Garcia, J. Ramon;Gasco-Hernandez, Mila
通讯作者：
Gasco-Hernandez, Mila

Period Estimation For Incomplete Time Series

DOI：
10.1109/dsaa49011.2020.00016
发表时间：
2020-10
期刊：
2020 IEEE 7th International Conference on Data Science and Advanced Analytics (DSAA)
影响因子：
0
作者：
Lin Zhang;Petko Bogdanov
通讯作者：
Lin Zhang;Petko Bogdanov

CORE: Connectivity Optimization via REinforcement Learning in WANETs

DOI：
10.1109/secon52354.2021.9491597
发表时间：
2021-07
期刊：
2021 18th Annual IEEE International Conference on Sensing, Communication, and Networking (SECON)
影响因子：
0
作者：
A. Gorovits;Karyn Doke;Lin Zhang;M. Zheleva;Petko Bogdanov
通讯作者：
A. Gorovits;Karyn Doke;Lin Zhang;M. Zheleva;Petko Bogdanov

AURORA: A Unified fRamework fOR Anomaly detection on multivariate time series.