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With the increasing use of autonomic computing technologies, JEE servers are implemented with more and more adaptive computations.
With the increasing use of autonomic computing technologies, a Java Enterprise Edition (JEE) application server is implemented with more and more adaptive computations for self-managing the Middleware as well as its hosted applications.
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Finally, a conclusion is drawn that the essence of autonomic computing is the automation of system adaptations for computing systems, which validates the synonymity between autonomic computing and adaptive computing, and comments are made upon the challenge of autonomic computing systems and the intrinsic differences between autonomic computing systems and conventional feedback control systems.
Firstly, an in-depth analysis is presented on the concept of autonomic computing and a generic architecture is put forward for autonomic computing systems.
These results are a first contribution towards deployment of autonomic computing concepts into BPM Business Process Managementt) architectures.
Thirdly, a brief survey is presented upon the states of the art of autonomic computing.
To address the previous issues, the concept of autonomic computing originated.
The major objectives of autonomic computing are to minimize human intervention and to enable a seamless self-adaptive behavior in the software systems.
The limitations of our research are constrained to the self-configuration property of autonomic computing.
How does the vision of autonomic computing satisfy the vision of self managing and self healing clouds?
Key questions to be addressed included: How do emerging cloud architectures satisfy or contradict the vision of autonomic computing?
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