Empirical resilience evaluation of an architecture-based self-adaptive software system



Architecture-based self-adaptation is considered as a promising approach to drive down the development and operation costs of complex software systems operating in ever changing environments. However, there is still a lack of evidence supporting the arguments for the beneficial impact of architecture-based self-adaptation on resilience with respect to other customary approaches, such as embedded code-based adaptation. In this paper, we report on an empirical study about the impact on resilience of incorporating architecture-based self-adaptation in an industrial middleware used to collect data in highly populated networks of devices. To this end, we compare the results of resilience evaluation between the original version of the middleware, in which adaptation mechanisms are embedded at the code-level, and a modified version of that middleware in which the adaptation mechanisms are implemented using Rainbow, a framework for architecture-based self-adaptation. Our results show improved levels of resilience in architecture-based compared to embedded code-based self-adaptation.

Related Project

ADAAS: Assuring Dependability in Architecture-based Adaptive Systems


QoSA '14 Proceedings of the 10th international ACM Sigsoft conference on Quality of software architectures 2014


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