Towards Self-adaptation Planning for Complex Service-Based Systems

A complex service-based system (CSBS), which comprises a multi-layer structure possibly spanning multiple organizations, operates in a highly dynamic and heterogeneous environment. At run time the quality of service provided by a CSBS may suddenly change, so that violations of the Service Level Agreements (SLAs) established within and across the boundaries of organizations can occur. Hence, a key management choice is to design the CSBS as a self-adaptive system, so that it can properly plan adaptation decisions to maintain the overall quality defined in the SLAs. However, the challenge in planning the CSBS adaptation is the uncertainty effect of adaptation actions that can variously affect the multiple layers of the CSBS. In a dynamic and constantly evolving environment, there is no guarantee that the adaptation action taken at a given layer can have an overall positive effect. Furthermore, the complexity of the cross-layer interactions makes the decision making process a non-trivial task. In this paper, we address the problem by proposing a multi-layer adaptation planning with local and global adaptation managers. The local manager is associated with a single planning model, while the global manager is associated with a multiple planning model. Both planning models are based on Markov Decision Processes (MDPs) that provide a suitable technique to model decisions under uncertainty. We present an example of scenario to show the practicality of the proposed approach.