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CNS Core: Small: Collaborative Research: HEECMA: A Hybrid Elastic Edge-Cloud Application Management Architecture

CNS Core: Small: Collaborative Research: HEECMA: A Hybrid Elastic Edge-Cloud Application Management Architecture
CNS 核心:小型:协作研究:HEECMA:混合弹性边缘云应用管理架构
批准号:
1908677
负责人:
Abraham Matta
金额:
$24.98万
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2019
资助国家:
美国
项目状态:
已结题
起止时间:
2019-10-01 至 2023-09-30

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中文摘要
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英文摘要
Application software is becoming increasingly abundant in functionality and increasingly demanding of resources, e.g., memory and compute power. This project examines how application software, e.g., a Virtual Reality (VR) based drone control application, can be partitioned and deployed over different parts of a distributed computing infrastructure, i.e., resources are managed by a hybrid of service and cloud providers. Research questions that will be answered include: what is the best partitioning of the application that balances compute and memory demand for each application component (function) and the communication needs between these functions? Which provider should be used for each application function so that it runs quickly at the lowest cost? Moreover, how should the system adapt to changes in the availability of resources to maintain a high level of quality of experience for users?The project will develop the theoretical foundations of decomposing applications over a distributed complex cyberinfrastructure. We will study various decompositions and corresponding virtualization and resource allocation services offered by different providers with resources at the edge of the infrastructure, i.e., closer to users, and at the core, i.e., deeper into the infrastructure. The goal is to find the "best" decomposition to meet users' quality of experience while reducing the cost/price for the users. The decomposed (distributed) solution will be realized by employing corresponding feedback control algorithms and game-theoretic incentives. The project will then experiment with three classes of applications to validate these theoretical foundations: streaming Augmented/Virtual Reality (AR/VR), intrusion detection, and spatiotemporal ecological forecasting. Toward this end, a prototype will be developed and evaluated over existing open cloud infrastructures (e.g., GENI, CloudLab, Chameleon), commercial clouds, as well as private clouds (e.g., Massachusetts Open Cloud).This project will advance the state of the art in the area of application software decomposition and deployment over large-scale hybrid cloud infrastructures. The theoretical foundations and experimental validation of the work will inform the design and deployment of other foreseen and unforeseen applications. The performance and cost gains will translate to more efficient use of resources and consequently, a society that is better connected and greener. Outreach efforts will include several activities: (1) the development and delivery of hands-on tutorials that involve partitioning and running application software over a distributed cyberinfrastructure managed by multiple providers, (2) the organization of annual summer camps on cyberinfrastructure operations and management for high school students, and (3) the training and mentoring of minority and under-represented students working on research related to this project. The project will maintain a website at http://csr.bu.edu/heecma for the duration of this grant and beyond. The website will contain all the publications and results of this project in the form of code, prototype, and tutorials.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.
期刊论文(9)
专著(0)
科研奖励(0)
会议论文
DOI: 10.1109/ic2e52221.2021.00028
发表时间: 2021-04
期刊: 2021 IEEE International Conference on Cloud Engineering (IC2E)
影响因子: --
作者: [A. Raza;Zongshun Zhang;Nabeel Akhtar;Vatche Isahagian;I. Matta]
通讯作者: A. Raza;Zongshun Zhang;Nabeel Akhtar;Vatche Isahagian;I. Matta
A Throughput Optimizing Scheduler for Multi-Cloud Serverless Computing
用于多云无服务器计算的吞吐量优化调度程序
DOI: --
发表时间: 2023
期刊: THE 14TH IEEE INTERNATIONAL CONFERENCE ON CLOUD COMPUTING TECHNOLOGY AND SCIENCE
影响因子: --
作者: [Mina Morcos, Ibrahim Matta]
通讯作者: Ibrahim Matta
DOI: 10.1109/tnsm.2023.3254437
发表时间: 2023-06-01
期刊: IEEE TRANSACTIONS ON NETWORK AND SERVICE MANAGEMENT
影响因子: 5.3
作者: [Raza, Ali, Akhtar, Nabeel, Huang, Lei]
通讯作者: Huang, Lei
DOI: 10.1109/tbdata.2023.3280405
发表时间: 2023-01
期刊: IEEE Transactions on Big Data
影响因子: 7.2
作者: [Zongshun Zhang;Andrea Pinto;Valeria Turina;Flavio Esposito;I. Matta]
通讯作者: Zongshun Zhang;Andrea Pinto;Valeria Turina;Flavio Esposito;I. Matta
7
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