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Creating good adaptation policies is critical to building complex autonomic systems since it is such policies that define the system configuration used in any given situation. While online approaches based on control theory and rule-based expert systems are possible solutions, each has its disadvantages. Here, a hybrid approach is described that uses modeling and optimization offline to generate suitable configurations, which are then encoded as policies that are used at runtime. The approach is demonstrated on the problem of providing dynamic management in virtualized consolidated server environments that host multiple multi-tier applications. Contributions include layered queuing models for Xen-based virtual machine environments, a novel optimization technique that uses a combination of bin packing and gradient search, and experimental results that show that automatic offline policy generation is viable and can be accurate even with modest computational effort.
Adaptation Policies, Server Consolidation, Layered Queueing Model, Optimization, Configuration, Multi-tier Applications

M. A. Hiltunen, G. Jung, C. Pu, K. R. Joshi and R. D. Schlichting, "Generating Adaptation Policies for Multi-tier Applications in Consolidated Server Environments," Autonomic Computing, International Conference on(ICAC), vol. 00, no. , pp. 23-32, 2008.
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