Integrating Goal Model into Rule-Based Adaptation

Goal-oriented adaptation provides a powerful mechanism to develop self-adaptive systems, enabling systems to keep satisfying user goals in a dynamically changing environment. The goal-oriented approach normally reduces the adaptation planning as a global optimization process and leaves the system the task of determining the actions required to achieve the goals. However, the high computation cost of global optimization prevents a self-adaptive system from quickly adjusting itself to the dynamically changing environment at runtime, which is intolerable since efficiency of planning is of utmost importance in most self-adaptive systems. On the other hand, rule-based adaptation has the advantage of efficient planning process since it predefines the adaptation logic by rules instead of leaving the system the task of reasoning. To combine the advantages of both approaches, we propose a novel adaptation framework that can integrate goal model into rule-based adaptation to make user goals to be better satisfied efficiently. We have applied the framework to design a self-adaptive e-commerce website. Our experimental results show that the proposed framework outperforms both the traditional goal-oriented approach and the traditional rule-based approach in terms of adaptation efficiency and effectiveness.