1st International IEEE Conference on Pervasive Services

Research Article

Automatic Reactive Adaptation of Pervasive Applications

  • @INPROCEEDINGS{10.1109/PERSER.2007.4283919,
        author={Marcus  Handte and Klaus  Herrmann and Gregor  Schiele and Christian Becker and Kurt Rothermel},
        title={Automatic Reactive Adaptation of Pervasive Applications},
        proceedings={1st International IEEE Conference on Pervasive Services},
        keywords={Adaptation model  Application software  Containers  Contracts  Cost function  Distributed computing  Pervasive computing  Power system modeling  Runtime environment},
  • Marcus Handte
    Klaus Herrmann
    Gregor Schiele
    Christian Becker
    Kurt Rothermel
    Year: 2007
    Automatic Reactive Adaptation of Pervasive Applications
    DOI: 10.1109/PERSER.2007.4283919
Marcus Handte1,*, Klaus Herrmann1,*, Gregor Schiele2,*, Christian Becker2,*, Kurt Rothermel3,*
  • 1: Universität Stuttgart, Germany
  • 2: Universität Mannheim, Germany
  • 3: Universität Stuttgart, German
*Contact email: marcus.handte@ipvs.uni-stuttgart.de, klaus.herrmann@ipvs.uni-stuttgart.de, gregor.schiele@uni-mannheim.de, christian.becker@uni-mannheim.de, kurt.rothermel@ipvs.uni-stuttgart.de


Pervasive computing envisions seamless and distraction-free support for everyday tasks through distributed applications that leverage the resources of the users' environment. Due to the mobility of users and devices, applications need to adapt continuously to their changing execution environment. Therefore, developers need a suitable framework in order to efficiently create adaptive applications. In this paper, we present and evaluate our approach to adapting a pervasive computing application to changes during its execution. This work is based on the minimal component system PCOM [2] and on an algorithm to fully automate the initial configuration of a component-based application [11] which we have presented in earlier work. The contribution of this paper is threefold. First, we describe a number of modifications to the component model that are required to enable fully automatic adaptation. Secondly, we propose a simple yet powerful cost model to capture the complexity of specific adaptations. Thirdly, we describe an online optimization heuristic that extends our distributed configuration algorithm in order to choose to a low-cost configuration whenever the current configuration of a pervasive application requires adaptation.