Hybrid Planning For Self-Adaptation

Self-adaptive software systems make decisions at run time that seek to change their behavior in response to faults, changing environments and attacks. Therefore, having an appropriate decision making approach to find an adaptation strategy is critical to successful self-adaptation. Ideally, when an adaptation is triggered, one would like to have a decision making approach that is both quick and finds an optimal adaptation strategy. However, often designers have to compromise between an approach that is quick to find an adaptation strategy and an approach that is slow but finds an optimal adaptation strategy. To deal with this trade-off between quick decision making and finding an optimal adaptation strategy, this position paper proposes a hybrid planning approach that combines more than one decision making approach to bring their benefits together. As an initial proof of concept, the paper presents the results of a small experiment to demonstrate the potential of a hybrid planning approach in dealing with this trade-off.