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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Ying Zhang Gang Huang Xuanzhe Liu Hong Mei |
| Copyright Year | 2011 |
| Abstract | In a cloud platform belonging to the PaaS (Platform as a Service) category, autonomic middleware have become the fundamental part of a cloud node. An autonomic middleware can perform adaptive computations for self-management of the system. However, these adaptive computations consume resources such as CPU and memory, and can interfere with each other and also with normal business functions of the system due to resource competition, especially when the system is under heavy load. As a result, the adaptive computations should be tuned from the perspective of resource management. In this position paper, we propose an approach to tuning the autonomic levels and thus controlling the resource costs of the adaptive computations in an autonomic middleware of PaaS cloud, so as to guarantee the system's performance when resources are competed. |
| Starting Page | 732 |
| Ending Page | 733 |
| File Size | 125040 |
| Page Count | 2 |
| File Format | |
| ISBN | 9781457708367 |
| ISSN | 21596190 |
| DOI | 10.1109/CLOUD.2011.66 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2011-07-04 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Tuners Adaptive systems Adaptive Computations Resource Competition Resource management Middleware Monitoring |
| Content Type | Text |
| Resource Type | Article |
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