An Adaptive Application Framework with Customizable Quality Metrics

Liu Liu, Sibren Isaacman, Ulrich Kremer

Research output: Contribution to journalArticlepeer-review

Abstract

Many embedded environments require applications to produce outcomes under different, potentially changing, resource constraints. Relaxing application semantics through approximations enables trading off resource usage for outcome quality. Although quality is a highly subjective notion, previous work assumes given, fixed low-level quality metrics that often lack a strong correlation to a user's higher-level quality experience. Users may also change their minds with respect to their quality expectations depending on the resource budgets they are willing to dedicate to an execution. This motivates the need for an adaptive application framework where users provide execution budgets and a customized quality notion. This article presents a novel adaptive program graph representation that enables user-level, customizable quality based on basic quality aspects defined by application developers. Developers also define application configuration spaces, with possible customization to eliminate undesirable configurations. At runtime, the graph enables the dynamic selection of the configuration with maximal customized quality within the user-provided resource budget.An adaptive application framework based on our novel graph representation has been implemented on Android and Linux platforms and evaluated on eight benchmark programs, four with fully customizable quality. Using custom quality instead of the default quality, users may improve their subjective quality experience value by up to 3.59×, with 1.76× on average under different resource constraints. Developers are able to exploit their application structure knowledge to define configuration spaces that are on average 68.7% smaller as compared to existing, structure-oblivious approaches. The overhead of dynamic reconfiguration averages less than 1.84% of the overall application execution time.

Original languageEnglish (US)
Article number13
JournalACM Transactions on Design Automation of Electronic Systems
Volume27
Issue number2
DOIs
StatePublished - Mar 2022
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Computer Graphics and Computer-Aided Design
  • Electrical and Electronic Engineering

Keywords

  • Approximate computing
  • configuration management
  • QoS

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