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Analysis of control-theoretic predictive strategies for the adaptation of distributed parallel computations
| Content Provider | ACM Digital Library |
|---|---|
| Author | Mencagli, Gabriele Vanneschi, Marco |
| Abstract | In adaptive distributed parallel applications the adaptation process is based on the ability to change some characteristics of parallel components, such as the parallelism form and the parallelism degree, in response to unexpected execution conditions. Although existing research work has studied this problem, it is of increasing importance to investigate adaptation strategies able to reach important properties like the stability of control decisions, i.e. to guarantee that reconfigurations are effective and durable, and control optimality, expressed by means of cooperative and non-cooperative agreements between decisions of different controllers. These properties are crucial in distributed environments like Grids and Clouds, where reconfigurations imply a cost both in terms of a performance degradation as well as a monetary charge. In this paper we briefly introduce the basic ideas of our methodology and we introduce different adaptation strategies based on alternative formulations of the Model-based Predictive Control technique. First hints about the effectiveness of our approach are discussed through experiments developed in a simulation environment. |
| Starting Page | 33 |
| Ending Page | 40 |
| Page Count | 8 |
| File Format | |
| ISBN | 9781450319829 |
| DOI | 10.1145/2465823.2465827 |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 2013-06-17 |
| Publisher Place | New York |
| Access Restriction | Subscribed |
| Subject Keyword | Reconfigurations Parallel computations Model-based predictive control Autonomic computing |
| Content Type | Text |
| Resource Type | Article |
