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Leveraging State-Based User Preferences in Context-Aware Reconfigurations for Self-Adaptive Systems

机译:在自适应系统的上下文感知重新配置中利用基于状态的用户首选项

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Applications in ubiquitous environments need to adapt to a range of fluid factors, like user preferences, context, and various system configurations. In this paper, we address the problem of system adaptation in order to continuously achieve high user benefit while keeping reconfiguration costs low. To this end, the presented approach leverages not only the immediate context but also future transitions. In contrast to existing approaches that either maximize benefit or minimize reconfiguration costs, our proposed decision support mechanism achieves a trade-off between those factors. Considering user preferences, deployment constraints, and probabilistic context state transitions, we propose a multi-objective utility function to determine the best reconfiguration choices. Experimental results show that the proposed approach achieves high user benefit while keeping reconfigurations costs low.
机译:无处不在的环境中的应用程序需要适应各种流体因素,例如用户偏好,上下文和各种系统配置。在本文中,我们解决了系统适应性问题,以便在保持较低的重新配置成本的同时,持续获得较高的用户利益。为此,所提出的方法不仅利用了即时环境,而且还利用了未来的过渡。与最大化收益或最小化重新配置成本的现有方法相反,我们提出的决策支持机制在这些因素之间进行了权衡。考虑到用户偏好,部署约束和概率性上下文状态转换,我们提出了一种多目标效用函数来确定最佳的重新配置选择。实验结果表明,该方法在保持较低的重新配置成本的同时,可实现较高的用户收益。

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