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    Non-intrusive In-situ Requirements Monitoring for Embedded Systems

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    Author
    Seo, Minjun
    Issue Date
    2018
    Keywords
    Embedded Systems
    In-situ
    Monitoring
    Non-intrusive
    Advisor
    Lysecky, Roman
    
    Metadata
    Show full item record
    Publisher
    The University of Arizona.
    Rights
    Copyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction, presentation (such as public display or performance) of protected items is prohibited except with permission of the author.
    Abstract
    Accounting for all operating conditions of a system at the design stage is typically infeasible for complex systems. Monitoring and verifying system requirements at runtime enable a system to continuously and introspectively ensure the system is operating correctly in the presence of dynamic execution scenarios. In this dissertation, we present a requirements-driven methodology enabling efficient system-level runtime monitoring of embedded systems. The presented methodology constructs a hierarchical runtime monitoring graph from system requirements specified using multiple UML sequence diagrams, which are already commonly used in software development, and state-based hardware models, which are common in hardware design. The requirements models for both software and hardware components can then be integrated to create a system-level requirements model that will be used at runtime to additionally verify the interactions between hardware and software components. Non-intrusive, on-chip hardware dynamically monitors the system-level execution and communication, verifies the execution and the communication adhere to the requirements model, and in the event of a failure provides detailed information that can be analyzed to determine the root cause. Using case studies of a collision-avoidance system and smart connect pacemaker prototypes, we analyze the relationship between event coverage, detection rate, detection latency, root cause analysis, and hardware requirements.
    Type
    text
    Electronic Dissertation
    Degree Name
    Ph.D.
    Degree Level
    doctoral
    Degree Program
    Graduate College
    Electrical & Computer Engineering
    Degree Grantor
    University of Arizona
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