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| Content Provider | ACM Digital Library |
|---|---|
| Author | Zoghi, Parisa Ghanbari, Hamoun Litoiu, Marin Shtern, Mark |
| Copyright Year | 2016 |
| 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. |
| Starting Page | 1 |
| Ending Page | 26 |
| Page Count | 26 |
| File Format | |
| ISSN | 15564665 |
| e-ISSN | 15564703 |
| DOI | 10.1145/2822896 |
| Volume Number | 10 |
| Issue Number | 4 |
| Journal | ACM Transactions on Autonomous and Adaptive Systems (TAAS) |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 2016-01-13 |
| Publisher Place | New York |
| Access Restriction | One Nation One Subscription (ONOS) |
| Subject Keyword | Adaptive systems Cloud computing Design Performance |
| Content Type | Text |
| Resource Type | Article |
| Subject | Control and Systems Engineering Software |
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