Affiliation:
1. York University, ON, Canada
Abstract
Designing an adaptive system to meet its quality constraints in the face of environmental uncertainties can be a challenging task. In a cloud environment, a designer has to consider and evaluate different control points, that is, those variables that affect the quality of the software system. This article presents a methodology for designing adaptive systems in cloud environments. The proposed methodology consists of several phases that take high-level stakeholders’ adaptation goals and transform them into lower-level MAPE-K loop control points. The MAPE-K loops are then activated at runtime using search-based algorithms. Our methodology includes the elicitation, ranking, and evaluation of control points, all meant to enable a runtime search-based adaptation. We conducted several experiments to evaluate the different phases of our methodology and to validate the runtime adaptation efficiency.
Funder
SAVI Strategic Research Network
Connected Vehicles and Smart Transportation
Natural Sciences and Engineering Research Council of Canada
Ontario Research Fund
Publisher
Association for Computing Machinery (ACM)
Subject
Software,Computer Science (miscellaneous),Control and Systems Engineering
Cited by
19 articles.
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