基于模型的自适应方法综述

自适应为管理现代软件系统的复杂性提供了有效的解决方案，被设计为自适应系统的软件能够持续的演化以应对环境中的不确定性.在现有的研究工作中，基于模型的自适应方法是一类广泛使用的方法，它将模型驱动工程技术的应用从设计时扩展到运行时以支持自适应能力的实现.通过利用软件模型对运行时丰富和不确定的信息进行管理，这类方法避免了将自适应逻辑与程序语言交织带来的复杂性，从而简化了自适应系统的开发.本文对近些年来国内外学者在该研究领域取得的成果进行了系统总结.首先，给出了六个研究问题，包括相关工作常用的需求模型、结构模型、行为模型、环境模型、模型与模型或模型与系统间的同步方式、自适应规划算法等；接着，依次总结了相关工作在这六个研究问题上的已有研究成果；最后，对未来研究可能面临的挑战进行了展望.

Survey of Model-Based Self-Adaptation Methods

Self-adaptation provides a promising approach to managing the complexity of modern software systems, and in particular, to enabling systems to continuously adapt themselves to uncertainty in the environment. In existing works, model-based self-adapatation is a kind of widely used methods that extend the applicability of model-driven engineering techqiques to the runtime environment to faciliate self-adaptation. By leveraging software models to manage the abundant information associated with runtime phenomena, model-based self-adaptation methods are able to avoid the complexity introduced by interwining adaptation and application behaviors and therefore simplify the development of self-adaptive systems. In this paper, we first come up with six research questions, concerning what system models, environment models, relationship among models, and model-based adaptation planning methods have been adopted by existing studies. We then answer the research questions by searching and investigating relevant studies. Finally, we give some suggestions for future research.