课题基金 / 基金详情

CRI: Emstar: A Community Resource for Heterogeneous Embedded Sensor Network Development

CRI: Emstar: A Community Resource for Heterogeneous Embedded Sensor Network Development
CRI:Emstar:异构嵌入式传感器网络开发的社区资源
批准号:
0453809
负责人:
Deborah Estrin
金额:
$0.0万
依托单位国家:
美国
项目类别:
Continuing Grant
财政年份:
2005
资助国家:
美国
项目状态:
已结题
起止时间:
2005-07-15 至 2009-06-30

项目摘要

项目成果

Deborah Estrin的其他基金

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中文摘要
翻译
无线嵌入式系统正在活跃CISE研究领域,从操作系统,分布式嵌入式计算,架构和网络到信号处理,算法和数据管理,并开辟了新的广泛影响的应用,从广域环境管理到生物医学监测。这些系统越来越多地集中在一个特别强大和令人兴奋的部署类别:异构或分层传感器网络。异构传感器网络包含具有不同功能的节点,例如微小的低功率“微尘”和高功率的“微服务器”。微尘价格低廉,不需要长期部署的基础设施,但在内存、CPU功率和通信方面也受到极大的限制。相比之下,微服务器在许多计算和内存密集型任务中比微尘更高效,并且更容易与高带宽外设(如高速ADC和网络接口)接口;但其更高的能耗需要电力基础设施,如太阳能电池板,长期部署。包含微尘和微服务器的异构系统可以联合收割机结合两种设备的优点,使用微尘来实现期望的空间感测密度,使用微服务器来实现期望的处理能力。无线嵌入式传感器系统提出了CISE社区的一系列相互交织的研究挑战:复杂多样的现象的真实的时间感测,嵌入式计算的带宽,能源,内存和存储,受控的移动性,以及大量的网络节点的自主协调。但是,即使不考虑这些挑战,实现和测试传感器网络应用也是令人生畏的:许多限制产生低功耗,长寿命的系统也破坏了传统的方法来检测和理解程序行为。因此,协调的社区基础设施可以作为一个巨大的研究加速器,没有共享的基础设施,该领域的研究将受到严重阻碍。该项目解决了一个迫切的需求:无线传感器网络的研究需要集中精力开发一个社区资源异构传感器systems.The调查人员将开发一个社区资源Emstar的基础上,一个高弹性的应用方法,微服务器和一般的异构部署。Emstar将模拟、仿真和部署顺利地结合在一起,从而使调试和应用程序分析在质量上更加容易。EmTOS组件无缝集成了mote和微服务器; EmView可视化工具为无线传感器网络通信模式提供了前所未有的可见性。这将建立在研究人员Emstar原型的基础上,Emstar原型已经证明了其在异构网络部署中的价值。通过扩展功能、集成、加固、增强可用性和长期支持,其广泛的工具将可供计算机和信息科学与工程界使用。该项目将扩大Emstar的灵活性、完整性、鲁棒性、文档和可编程性;通过从地震阵列、移动的环境传感和医疗信息学等目标部署中学习来扩展其功能;并通过研讨会、教程和邮件列表开发一个强大、活跃的Emstar社区。 拟议的社区资源将作为异构无线传感器网络研究的巨大加速器,使快速和彻底的探索社会重要的应用,包括环境监测,医疗和公共卫生系统,以及工业和民用基础设施的发展和管理。该项目还将支持和开发使用Emstar的本科生和研究生项目课程,并明确涉及针对代表性不足的少数民族的本科生研究计划。
英文摘要
Wireless embedded systems are invigorating CISE research areas from operating systems, distributed embedded computing, architecture, and networking to signal processing, algorithms, and data management, and opening up new broad-impact applications ranging from wide area environmental management to biomedical monitoring. These systems are increasingly focused on a particularly powerful and exciting class of deployment: the heterogeneous or tiered sensor network. A heterogeneous sensor network contains nodes with different capabilities, such as tiny, low-power "motes" and higher-powered, "microservers". Motes are inexpensive and require no infrastructure for long-term deployments, but also extremely constrained in memory, CPU power, and communication. Microservers, in contrast, are more efficient than motes at many computation- and memory-intensive tasks, and more readily interfaced to high-bandwidth peripherals, such as high-rate ADCs and network interfaces; but their higher energy consumption requires power infrastructure, such as solar panels, in long-term deployments. A heterogeneous system containing both motes and microservers can combine the advantages of both devices, using motes to achieve the desired spatial sensing density and microservers to achieve the desired processing power. Wireless embedded sensor systems present the CISE community with an array of intertwined research challenges: real time sensing of complex and diverse phenomena, embedded computing constrained in bandwidth, energy, memory, and storage, controlled mobility, and the autonomous coordination of vast numbers of network nodes. But implementing and testing sensor network applications is daunting even aside from these challenges: many of the constraints that yield low-power, long-lifetime systems also undermine traditional methods for instrumenting and understanding program behavior. Coordinated community infrastructure can thus act as a tremendous research accelerator, and without shared infrastructure, research in the field will be significantly hampered. This project addresses a pressing need: wireless sensor network research demands a concentrated effort to develop a community resource for heterogeneous sensor systems.The investigators will develop a community resource based on Emstar, a highly resilient application methodology for microservers and general heterogeneous deployments. Emstar smoothly combines simulation, emulation, and deployment, leading to qualitatively easier debugging and application analysis. An EmTOS component seamlessly integrates motes and microservers; the EmView visualizer provides unprecedented visibility into wireless sensor network communication patterns.This will build on the investigators Emstar prototype which has proven its value in deployments of heterogeneous networks.With expanded functionality, integration, hardening, enhanced usability, and longer-term support, its broad array of tools will become accessible to the computer and information science and engineering community. The project will expand Emstar's flexibility, completeness, robustness, documentation, and programmability; extend its functionality by learning from targeted deployments such as seismic arrays, mobile environmental sensing, and medical informatics; and develop a robust, active Emstar community through workshops, tutorials, and mailing lists. The proposed community resource will act as a tremendous accelerator for research into heterogeneous wireless sensor networks, enabling quick and thorough exploration of socially important applications including environmental monitoring, medical and public health systems, and industrial and civic infrastructure development and management. The project will also support and develop undergraduate and graduate level project courses using Emstar, and explicitly involve an undergraduate research program targeting underrepresented minorities.
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会议论文
CHS: Medium: Immersive Recommendation Systems: User-Centric Recommendation Models and Applications
  • 批准号:
    1700832
  • 项目类别:
    Continuing Grant
  • 资助金额:
    $120.0万
  • 财政年份:
    2017
  • 负责人:
    Deborah Estrin
  • 依托单位:
EAGER: Collaborative: A Research Agenda to Explore Privacy in Small Data Applications
  • 批准号:
    1536897
  • 项目类别:
    Standard Grant
  • 资助金额:
    $5.4万
  • 财政年份:
    2015
  • 负责人:
    Deborah Estrin
  • 依托单位:
Small Data Research Infrastructure: Workshop Proposal
  • 批准号:
    1451448
  • 项目类别:
    Standard Grant
  • 资助金额:
    $9.71万
  • 财政年份:
    2014
  • 负责人:
    Deborah Estrin
  • 依托单位:
SCH: INT: Novel Techniques for Patient-centric Disease Management using Automatically Inferred Behavioral Biomarkers and Sensor-Supported Contextual Self-Report
  • 批准号:
    1344587
  • 项目类别:
    Standard Grant
  • 资助金额:
    $197.7万
  • 财政年份:
    2013
  • 负责人:
    Deborah Estrin
  • 依托单位: