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HDCCSR: Scalable Dependability in Componentized Software via Self-Stabilization

HDCCSR: Scalable Dependability in Componentized Software via Self-Stabilization
HDCCSR:通过自稳定实现组件化软件的可扩展可靠性
批准号:
0341703
负责人:
Anish Arora
金额:
$48.01万
依托单位国家:
美国
项目类别:
Continuing Grant
财政年份:
2003
资助国家:
美国
项目状态:
已结题
起止时间:
2003-09-15 至 2007-08-31

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英文摘要
----------------------Scalable Dependability in Componentized Software via Self-StabilizationPI: Anish Arora, Professor, CIS, The Ohio State UniversityThis proposal addresses the problem of unanticipated software faults, which inevitably occur in large-scale software systems, including those used by the United States space program for missions such as the International Space Station, by developing tools and frameworksfor self-stabilization, i.e., for restoring system behavior if it deviates from its intended one by detecting and correcting state predicates.Extant techniques for designing/composing stabilizing systems do notscale well. The proposed research addresses complexity as follows.- A component is typically simpler than the system as a whole. Hencestabilization will be added per component and then they will be composed into a stabilizing system, taking into account issues of dependency and interference.- A component's specification is usually simpler than the component itself.hence stabilization will be added per component with respect to only the component specification, The proposed research will demonstrate that the software tools and frameworks resulting from these ideas measurably and predictably improve dependability in a NASA system. The techniques and tools will provide for the first time the ability to make large systems tolerant to unanticipated faults. Besides space craft, they can also be used with critical systems such as aircraft control,medical instruments, the telephone network, etc.
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CC*: Integration-Large: POWWOW: Software-Defined Infrastructure for Wireless, Edge Cybersecurity Testbeds
  • 批准号:
    2018912
  • 项目类别:
    Standard Grant
  • 资助金额:
    $75.0万
  • 财政年份:
    2020
  • 负责人:
    Anish Arora
  • 依托单位:
EAGER: Collaborative Research: III: Exploring Physics Guided Machine Learning for Accelerating Sensing and Physical Sciences
  • 批准号:
    2026704
  • 项目类别:
    Standard Grant
  • 资助金额:
    $5.02万
  • 财政年份:
    2020
  • 负责人:
    Anish Arora
  • 依托单位:
PC3: Collaborative Research: Wireless Sensor Networks for Protecting Wildlife and Humans
  • 批准号:
    1143685
  • 项目类别:
    Standard Grant
  • 资助金额:
    $17.82万
  • 财政年份:
    2011
  • 负责人:
    Anish Arora
  • 依托单位:
CPS:Small:Collaborative Research:Localization and System Services for SpatioTemporal Actions in Cyber-Physical Systems
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Scalable Learning and Optimization: High-dimensional Models and Online Decision-Making Strategies for Big Data Analysis