The concepts that make self-adaptive software attractive also make it more difficult for users to gain confidence that these systems will consistently meet their goals under uncertain context. To improve user confidence in self-adaptive behavior, machine-readable conceptual models have been developed to instrument the adaption behavior of the target software system and primary feedback loop. By comparing these machine-readable models to the self-adaptive system, runtime verification and validation may be introduced as another method to increase confidence in self-adaptive systems; however, the existing conceptual models do not provide the semantics needed to institute this runtime verification or validation. This research confirms that the introduction of runtime verification and validation for self-adaptive systems requires the expansion of existing conceptual models with quality of service metrics, a hierarchy of goals, and states with temporal transitions. Based on this expanded semantics, runtime verification and validation was introduced as a second-level feedback loop to improve the performance of the primary feedback loop and quantitatively measure the quality of service achieved in a state-based, self-adaptive system. A web-based purchasing application running in a cloud-based environment was the focus of experimentation. In order to meet changing customer purchasing demand, the self-adaptive system monitored external context changes and increased or decreased available application servers. The runtime verification and validation system operated as a second-level feedback loop to monitor quality of service goals based on internal context, and corrected self-adaptive behavior when goals are violated. Two competing quality of service goals were introduced to maintain customer satisfaction while minimizing cost. The research demonstrated that the addition of a second-level runtime verification and validation feedback loop did quantitatively improve self-adaptive system performance even with simple, static monitoring rules.
| Identifer | oai:union.ndltd.org:nova.edu/oai:nsuworks.nova.edu:gscis_etd-1997 |
| Date | 01 January 2017 |
| Creators | Sayre, David B. |
| Publisher | NSUWorks |
| Source Sets | Nova Southeastern University |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | CEC Theses and Dissertations |
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