XPS: FULL: Collaborative Research: Enabling Scalable Cloud And Edge-device Integration Using Cross-layer Parallelism
XPS:完整:协作研究:使用跨层并行性实现可扩展的云和边缘设备集成
基本信息
- 批准号:1629347
- 负责人:
- 金额:$ 24.7万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Standard Grant
- 财政年份:2016
- 资助国家:美国
- 起止时间:2016-09-01 至 2018-12-31
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
The importance of energy efficiency today is felt across all domains of computing. In particular, personal computing platforms are becoming increasingly wireless and miniaturized, but limited by trade-offs between battery lifetimes and computational requirements. Developing energy-efficient solutions is critical to the survival of the semiconductor industry. This project seeks to develop new abstractions to effectively utilize network and cloud resources to enable a scalable and energy-efficient mobile computing paradigm. The proposed hierarchical cloud computing architecture with cross-layer parallelism provides innovation for teaching networking, system, and architecture courses. It provides a platform to engage undergraduate students and community service agencies. Finally, this project is expected to have a high impact on global societies and economies.The proposed distributed system architecture leverages cross-layer parallelism to enable scalable, adaptive, and intelligent integration between edge mobile devices and clouds by intelligently partitioning and replicating computation between mobile devices and the cloud. This project redefines two classes of programming abstractions that enable seamless usage of: (1) network resources at transport layers and (2) any form of cloud resources whether local or remote. The proposed architecture strategically leverages network-level parallelism that transparently utilizes multiple network paths, in-network cloudlets that offer highly customized accelerators for offloaded computation, and remote cloud servers with more plentiful resources. These three components work in a coordinated way with awareness of the dynamic communication overhead, thereby ensuring scalability and energy efficiency of supporting both compute and network intensive distributed applications on mobile platforms.
如今,能源效率的重要性在所有计算领域都能感受到。 特别是,个人计算平台正变得越来越无线和小型化,但受到电池寿命和计算要求之间的权衡的限制。开发节能解决方案对于半导体行业的生存至关重要。该项目旨在开发新的抽象,以有效地利用网络和云资源,使一个可扩展的和节能的移动的计算范例。 所提出的具有跨层并行性的分层云计算架构为网络、系统和架构课程的教学提供了创新。它提供了一个平台,让本科生和社区服务机构参与。该分布式系统架构利用跨层并行性,通过在移动的设备和云之间智能地划分和复制计算,实现边缘移动的设备和云之间的可扩展、自适应和智能集成。 该项目重新定义了两类编程抽象,可以无缝使用:(1)传输层的网络资源和(2)任何形式的云资源,无论是本地还是远程。 所提出的架构战略性地利用了网络级并行性,该并行性透明地利用了多个网络路径、为卸载计算提供高度定制的加速器的网络内云以及具有更丰富资源的远程云服务器。这三个组件以协调的方式工作,并意识到动态通信开销,从而确保在移动的平台上支持计算和网络密集型分布式应用的可扩展性和能量效率。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Feng Qian其他文献
A extreme learning machines approach for accurate estimation of large-scale IP network traffic matrix
一种精确估计大规模IP网络流量矩阵的极限学习机方法
- DOI:
- 发表时间:
2012 - 期刊:
- 影响因子:0
- 作者:
Feng Qian;Tao Lian;Jiaxing Wu - 通讯作者:
Jiaxing Wu
Investigating the coupling between phytoplankton biomass, aerosol optical depth and sea-ice cover in the Greenland Sea
研究格陵兰海浮游植物生物量、气溶胶光学深度和海冰覆盖之间的耦合
- DOI:
10.1016/j.dynatmoce.2014.03.001 - 发表时间:
2014-06 - 期刊:
- 影响因子:1.7
- 作者:
Hailang Lu;Dao Rong Lin;Feng Qian;Min Zhao - 通讯作者:
Min Zhao
Unsupervised Estimation of Monocular Depth and VO in Dynamic Environments via Hybrid Masks
通过混合掩模对动态环境中的单眼深度和 VO 进行无监督估计
- DOI:
- 发表时间:
2021 - 期刊:
- 影响因子:10.4
- 作者:
Qiyu Sun;Yang Tang;Chongzhen Zhang;Chaoqiang Zhao;Feng Qian;Jürgen Kurths - 通讯作者:
Jürgen Kurths
Oscillatory behavior of a class impulsive fractional partial differential equation
一类脉冲分数阶偏微分方程的振荡行为
- DOI:
- 发表时间:
2020 - 期刊:
- 影响因子:0
- 作者:
Feng Qian;Liu Anping - 通讯作者:
Liu Anping
Reversible Swarming of Micro Robots Controlled by Acoustic Field
声场控制微型机器人的可逆集群
- DOI:
- 发表时间:
2022 - 期刊:
- 影响因子:0
- 作者:
Cong Zhao;Hu Ou;Lukai Shi;Ying Wei;Feng Qian;Xiaolong Lu - 通讯作者:
Xiaolong Lu
Feng Qian的其他文献
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{{ truncateString('Feng Qian', 18)}}的其他基金
Conference: ACM SIGCOMM 2023 Travel Grant
会议:ACM SIGCOMM 2023 旅行补助金
- 批准号:
2335184 - 财政年份:2023
- 资助金额:
$ 24.7万 - 项目类别:
Standard Grant
Collaborative Research: CNS Core: Medium: Innovating Volumetric Video Streaming with Motion Forecasting, Intelligent Upsampling, and QoE Modeling
合作研究:CNS 核心:中:通过运动预测、智能上采样和 QoE 建模创新体积视频流
- 批准号:
2409008 - 财政年份:2023
- 资助金额:
$ 24.7万 - 项目类别:
Continuing Grant
Collaborative Research: SaTC: CORE: Medium: Audacity of Exploration: Toward Automated Discovery of Security Flaws in Networked Systems through Intelligent Documentation Analysis
协作研究:SaTC:核心:中:大胆探索:通过智能文档分析自动发现网络系统中的安全缺陷
- 批准号:
2409269 - 财政年份:2023
- 资助金额:
$ 24.7万 - 项目类别:
Standard Grant
CPS: Medium: Collaborative Research: Transforming Connected and Automated Transportation with Smart Networking, Cooperative Sensing, and Edge Computing
CPS:中:协作研究:通过智能网络、协作传感和边缘计算改变互联和自动化交通
- 批准号:
2409271 - 财政年份:2023
- 资助金额:
$ 24.7万 - 项目类别:
Standard Grant
Collaborative Research: CNS Core: Medium: Innovating Volumetric Video Streaming with Motion Forecasting, Intelligent Upsampling, and QoE Modeling
合作研究:CNS 核心:中:通过运动预测、智能上采样和 QoE 建模创新体积视频流
- 批准号:
2212298 - 财政年份:2022
- 资助金额:
$ 24.7万 - 项目类别:
Continuing Grant
Collaborative Research: SaTC: CORE: Medium: Audacity of Exploration: Toward Automated Discovery of Security Flaws in Networked Systems through Intelligent Documentation Analysis
协作研究:SaTC:核心:中:大胆探索:通过智能文档分析自动发现网络系统中的安全缺陷
- 批准号:
2154078 - 财政年份:2022
- 资助金额:
$ 24.7万 - 项目类别:
Standard Grant
Collaborative Research: CNS Core: Medium: Foundations and Scalable Algorithms for Personalized and Collaborative Virtual Reality Over Wireless Networks
协作研究:CNS 核心:中:无线网络上个性化和协作虚拟现实的基础和可扩展算法
- 批准号:
2106090 - 财政年份:2021
- 资助金额:
$ 24.7万 - 项目类别:
Continuing Grant
CPS: Medium: Collaborative Research: Transforming Connected and Automated Transportation with Smart Networking, Cooperative Sensing, and Edge Computing
CPS:中:协作研究:通过智能网络、协作传感和边缘计算改变互联和自动化交通
- 批准号:
2038559 - 财政年份:2021
- 资助金额:
$ 24.7万 - 项目类别:
Standard Grant
XPS: FULL: Collaborative Research: Enabling Scalable Cloud And Edge-device Integration Using Cross-layer Parallelism
XPS:完整:协作研究:使用跨层并行性实现可扩展的云和边缘设备集成
- 批准号:
1903880 - 财政年份:2018
- 资助金额:
$ 24.7万 - 项目类别:
Standard Grant
CAREER: Improving Mobile Video Delivery for Emerging Contents and Networks
职业:改进新兴内容和网络的移动视频传输
- 批准号:
1915122 - 财政年份:2018
- 资助金额:
$ 24.7万 - 项目类别:
Continuing Grant
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钴基Full-Heusler合金的掺杂效应和薄膜噪声特性研究
- 批准号:51871067
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