NeTS: Small: Fundamental Techniques for Incentive-aware, Efficient, and Reliable Cloudlet Management and Services

NetS：小型：激励感知、高效且可靠的 Cloudlet 管理和服务的基本技术

• 批准号: 1526843
• 负责人: Xin Wang
• 金额: $ 44.12万
• 依托单位: SUNY at Stony Brook
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-10-01 至 2019-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1526843&HistoricalAwards=false
• 关键词: NeTS; Small; Fundamental; Techniques; Incentive

The goal of this work is to develop some fundamental techniques that can facilitate efficient management of cloudlet resources for high cloud service performance while minimizing the system cost. These techniques are to enable efficient, reliable and low cost mobile cloud services, which will in turn support high-performance wireless applications in an energy- and resource efficient manner. With this research, a cloud service provider can exploit sparse signal processing technique to remotely monitor one or multiple cloudlet clusters running in different location sites with high accuracy but low cost. To reduce the service initialization delay and operational cost, the system can cache application components, and a user can exploit the proposed rate dependent Bloom filter (RDBF) to quickly determine of some cloudlets have its required application components cached. Rather than being constrained by a limited number of options for virtual machine (VM) configurations, the system will be equipped with multi-dimensional pricing and resource negotiation capabilities for a user to flexibly negotiate multiple types of resources to maximize the benefits of both users and cloudlets while taking into account user application preference, performance requirements, and the system resource conditions. Complementary to the research agenda, the project will carry out a broad range of education and outreach activities and facilitate technology transfer through the industrial partners and industry affiliate programs. The proposed research is part of a global effort in exploiting (mobile) cloud computing for advancing some critical fields for national economy and security, including health-care, transportation, smart-grid, homeland security, and education.

这项工作的目的是开发一些基本技术，这些技术可以促进有效地管理Cloudlet资源，以促进高云服务性能，同时最大程度地降低系统成本。这些技术是为了实现高效，可靠和低成本的移动云服务，这又将以能源和资源有效的方式支持高性能无线应用程序。通过这项研究，云服务提供商可以利用稀疏的信号处理技术来远程监视一个或多个Cloudlet群集在不同的位置站点运行的一个或低成本，但成本低。为了减少服务初始化延迟和操作成本，该系统可以缓存应用程序组件，并且用户可以利用拟议的费用依赖的布鲁姆过滤器（RDBF）快速确定某些Cloudlet具有所需的应用程序组件。该系统将不受虚拟机（VM）配置的数量有限的选项来限制，而是配备了多维定价和资源谈判能力，使用户可以灵活地协商多种类型的资源，以最大程度地利用用户和Cloudlet的收益，同时考虑到Excelly Epplication Applice应用程序的应用程序偏好，绩效要求，系统资源和系统条件。互补的研究议程将进行广泛的教育和外展活动，并通过工业伙伴和行业会员计划促进技术转移。拟议的研究是全球开发（移动）云计算的努力的一部分，以推动一些针对国民经济和安全的关键领域，包括医疗保健，运输，智能网格，国土安全和教育。