Model-based Autonomic and Performance-aware System Adaptation in Heterogeneous Resource Environments: A Case Study
Proceedings of the 2015 IEEE International Conference on Cloud and Autonomic Computing (ICCAC), IEEE, (September 2015)Abstract
Recent trends like cloud computing show that service providers increasingly adopt to modern self-adaptive system architectures promising higher resource efficiency and lower operating costs. Blue Yonder is such a service provider in the field of predictive analytics, looking for novel approaches to automatically adapt their service infrastructure to changing customer workloads and service-level agreements. In this paper, we present a realistic case study in which we apply a holistic modelbased approach to build a self-adaptive system that automatically maintains performance requirements and resource efficiency in the heterogeneous resource environment of Blue Yonder. As modeling formalism, we employ the Descartes Modeling Language (DML), a domain-specific language for modeling the performance behavior and run-time adaptation processes of modern dynamic IT systems. This case study is an exemplar for applying a holistic model-based approach to engineering performance-aware system adaptation. More specifically, the results evaluate the applicability and effectiveness of our approach and demonstrate that DML provides suitable modeling abstractions that can be used as a basis for self-adaptive performance and resource management.
