CSR: EAGER: Collaborative Research: Brokerage Services for the Next Generation Cloud
CSR:EAGER:协作研究:下一代云的经纪服务
基本信息
- 批准号:1250327
- 负责人:
- 金额:$ 14.03万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Standard Grant
- 财政年份:2012
- 资助国家:美国
- 起止时间:2012-09-01 至 2014-08-31
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
Future cloud services are expected to increasingly involve and synthesize capabilities from multiple clouds. Applications from different organizations may establish collaborative relationships and share information dynamically in cloud computing. In this increasingly complex scenario, both consumers and service providers will face new challenges. For example, consumers will need to be able to identify the best service providers from a potentially huge pool, which could be computationally demanding. Service providers will need to be able to ensure the security and privacy of data shared among loosely connected subcontractors.This project proposes a novel brokerage-based architecture to promote cost-effective cloud provisioning. Specifically, the PIs will devise efficient indexing structures to facilitate the management of massive information generated by a large number of service providers with a variety of properties. The PIs are developing necessary services to allow effective cloud-brokerage, such as service selection for consumers, service negotiation between consumers and their service providers, and service agreement delegation among service providers involved in a compound service. Along with the service development, the work will produce new policy analysis, composition and delegation techniques that accommodate the unique characteristics of the cloud.The research in this project will help significantly streamline the selection and management of cloud computing services, and will open up new business opportunities by providing cloud brokerage services. Moreover, the proposed approach may also help reduce the vendor lock-in problem which is a long standing major concern among consumers.
预计未来的云服务将越来越多地参与并综合来自多个云的功能。来自不同组织的应用程序可以建立协作关系并在云计算中动态共享信息。在这种日益复杂的情况下,消费者和服务提供商都将面临新的挑战。例如,消费者将需要能够从潜在的巨大池中识别出最佳的服务提供商,这可能是计算要求的。服务提供商将需要能够确保在松散连接的分包商中共享数据的安全性和隐私。本项目提出了一种基于经纪的新型体系结构,以促进具有成本效益的云提供。具体而言,PI将设计有效的索引结构,以促进由许多具有多种属性的服务提供商生成的大量信息的管理。 PI正在开发必要的服务,以允许有效的云经纪,例如为消费者及其服务提供商之间的服务谈判以及参与复合服务的服务提供商之间的服务协议代表团。除服务开发外,这项工作还将产生新的政策分析,组成和代表团技术,以适应云的独特特征。该项目的研究将有助于简化云计算服务的选择和管理,并将开放新的新通过提供云经纪服务通过提供商机。此外,拟议的方法还可以帮助减少供应商的锁定问题,这是消费者长期以来的主要关注点。
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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Dan Lin其他文献
Exploration of role of market in perishable goods
探索市场在易腐烂商品中的作用
- DOI:
- 发表时间:
2007 - 期刊:
- 影响因子:0
- 作者:
Dan Lin - 通讯作者:
Dan Lin
Cointegration analysis of tourism demand by Mainland China in Taiwan and stock investment strategy
中国大陆赴台旅游需求协整分析及股票投资策略
- DOI:
10.18533/jefs.v3i06.163 - 发表时间:
2015 - 期刊:
- 影响因子:0
- 作者:
Yu;Dan Lin;Lu Lin - 通讯作者:
Lu Lin
Multidimensional Parallelization for Streaming Text Processing Applications Based on Parabix Framework
基于Parabix框架的流式文本处理应用的多维并行化
- DOI:
- 发表时间:
2017 - 期刊:
- 影响因子:0
- 作者:
Dan Lin - 通讯作者:
Dan Lin
Using baseline gene expression for multi-Compound screening in early drug development experiments.
在早期药物开发实验中使用基线基因表达进行多化合物筛选。
- DOI:
- 发表时间:
2008 - 期刊:
- 影响因子:0
- 作者:
Adetayo S Kasim;Dan Lin;Z. Shkedy;W. Talloen;L. Bijnens - 通讯作者:
L. Bijnens
Confidence and Prediction in Linear Mixed Models: Do Not Concatenate the Random Effects. Application in an Assay Qualification Study
线性混合模型中的置信度和预测:不要连接随机效应。
- DOI:
- 发表时间:
2020 - 期刊:
- 影响因子:0
- 作者:
B. Francq;Dan Lin;W. Hoyer - 通讯作者:
W. Hoyer
Dan Lin的其他文献
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{{ truncateString('Dan Lin', 18)}}的其他基金
Collaborative Research: SaTC: CORE: Medium: Broad-Spectrum Facial Image Protection with Provable Privacy Guarantees
合作研究:SaTC:核心:中:具有可证明隐私保证的广谱面部图像保护
- 批准号:
2301014 - 财政年份:2022
- 资助金额:
$ 14.03万 - 项目类别:
Standard Grant
Collaborative Research: SaTC: CORE: Medium: Self-Learning and Self-Evolving Detection of Altered, Deceptive Images and Videos
协作研究:SaTC:核心:媒介:篡改、欺骗性图像和视频的自学习和自进化检测
- 批准号:
2243161 - 财政年份:2022
- 资助金额:
$ 14.03万 - 项目类别:
Standard Grant
Collaborative Research: SaTC: CORE: Medium: Broad-Spectrum Facial Image Protection with Provable Privacy Guarantees
合作研究:SaTC:核心:中:具有可证明隐私保证的广谱面部图像保护
- 批准号:
2114141 - 财政年份:2021
- 资助金额:
$ 14.03万 - 项目类别:
Standard Grant
Collaborative Research: SaTC: CORE: Medium: Self-Learning and Self-Evolving Detection of Altered, Deceptive Images and Videos
协作研究:SaTC:核心:媒介:篡改、欺骗性图像和视频的自学习和自进化检测
- 批准号:
2027398 - 财政年份:2020
- 资助金额:
$ 14.03万 - 项目类别:
Standard Grant
EAGER: TWC: Collaborative: iPrivacy: Automatic Recommendation of Personalized Privacy Settings for Image Sharing
EAGER:TWC:协作:iPrivacy:自动推荐图像共享的个性化隐私设置
- 批准号:
1852554 - 财政年份:2018
- 资助金额:
$ 14.03万 - 项目类别:
Standard Grant
EAGER: TWC: Collaborative: iPrivacy: Automatic Recommendation of Personalized Privacy Settings for Image Sharing
EAGER:TWC:协作:iPrivacy:自动推荐图像共享的个性化隐私设置
- 批准号:
1651455 - 财政年份:2016
- 资助金额:
$ 14.03万 - 项目类别:
Standard Grant
MASTER: Missouri Advanced Security Training, Educa
硕士:密苏里州高级安全培训,Educa
- 批准号:
1433659 - 财政年份:2014
- 资助金额:
$ 14.03万 - 项目类别:
Continuing Grant
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