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Automated Model-Based Optimization of Data-Adaptable Embedded Systems

Published: 06 February 2020 Publication History

Abstract

Dynamic data-driven applications such as object tracking, surveillance, and other sensing and decision applications are largely dependent on the characteristics of the data streams on which they operate. The underlying models and algorithms of data-driven applications must continually adapt at runtime to changes in data quality and availability to meet both functional and designer-specified performance requirements. Given the dynamic nature of these applications, point solutions produced by traditional design tools cannot be expected to perform adequately across varying execution scenarios. Additionally, the increasing diversity and interdependence of application requirements complicates the design and optimization process. To assist designers of data-driven applications, we present a modeling and optimization framework that enables developers to model an application's data sources, tasks, and exchanged data tokens; specify application requirements through high-level design metrics and fuzzy logic--based optimization rules; and define an estimation framework to automatically optimize the application at runtime. We demonstrate the modeling and optimization process via an example application for video-based vehicle tracking and collision avoidance. We analyze the benefits of runtime optimization by comparing the performance of static point solutions to dynamic solutions over five distinct execution scenarios, showing improvements of up to 74% for dynamic over static configurations. Further, we show the benefits of using fuzzy logic--based rules over traditional weighted functions for the specification and evaluation of competing high-level metrics in optimization.

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    cover image ACM Transactions on Embedded Computing Systems
    ACM Transactions on Embedded Computing Systems  Volume 19, Issue 1
    January 2020
    185 pages
    ISSN:1539-9087
    EISSN:1558-3465
    DOI:10.1145/3382497
    Issue’s Table of Contents
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    Publication History

    Published: 06 February 2020
    Accepted: 01 November 2019
    Revised: 01 August 2018
    Received: 01 December 2017
    Published in TECS Volume 19, Issue 1

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    Author Tags

    1. Software modeling
    2. design space exploration
    3. dynamic data-driven systems
    4. dynamic optimization
    5. fuzzy logic--based optimization rules

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    • (2022)An adaptive genetic algorithm-based background elimination model for English textSoft Computing - A Fusion of Foundations, Methodologies and Applications10.1007/s00500-022-07204-726:16(8133-8143)Online publication date: 1-Aug-2022

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