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The goal of autonomic computing is to reduce the increasing complexity of managing large computing systems. As computing systems evolve, they are subject to the effect of continuous growth in the number of degrees of freedom that must be well-managed in order to maintain their efficiency. Two major factors contribute to the increase in the number of degrees of freedom. One is the different rates at which the capabilities of computing elements, such as the CPU, memory, disks, and networks, have historically increased. The disparity between the capabilities of various elements provides opportunities to use different strategies for a task, depending upon the environment. In turn, this calls for a dynamic approach in order to make judicious choices for achieving targeted efficiency. The other factor is the tendency of current systems to exhibit a global range in the demand for their services and the resources they employ for rendering the services. Changes in the demands or resources in one part of a system can have a significant effect on other parts of the system.
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