Friday 29th of March 2024
 

A Self-Optimization Method for System Service Dependability based on Autonomic Computing


Qingtao Wu, Lina Zhu, Ying Lou and Ruijuan Zheng

Under the intrusion or abnormal attacks, how to supply system service dependability autonomously, without being degraded, is the essential requirement to network system service. Autonomic Computing can overcome the heterogeneity and complexity of computing system, has been regarded as a novel and effective approach to implementing autonomous systems to address system security issues. To cope with the problem of declining network service dependability caused by safety threats, we proposed an autonomic method for optimizing system service performance based on Q-learning from the perspective of autonomic computing. First, we get the operations by utilizing the nonlinear mapping relations of the feedforward neural network. Then, we obtain the executive action by perceiving the state parameter changes of the network system in the service performance. Thirdly, we calculate the environment-rewarded function value integrated the changes of the system service performance and the service availability. Finally, we use the self-learning characteristics and prediction ability of the Q-learning to make the system service to achieve optimal performance. Simulation results show that this method is effective for optimizing the overall dependability and service utility of a system.

Keywords: Autonomic Computing, Service Dependability, Feedforward Neural Network, Q-learning Algorithm

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ABOUT THE AUTHORS

Qingtao Wu
got his PhD degree in computer science from East China University of Science and Technology, in 2006, on network and information security. He\'s Associate Professor in Computer Science at Electronic & Information Engineering College of Henan University of Science and Technology, China. He\'s currently managing and leading 2 projects supported by the National Natural Science Foundation of China to address the autonomic mechanism for the retainment and enhancement of system security. His main research interests include computer system security, intelligent information processing, etc.

Lina Zhu
received her Bachelor\'s degree in Computer Science and Technology in 2010. She is currently a Master Degree Candidate directed by Dr. Qingtao Wu in Computer Science at Electronic & Information Engineering College of Henan University of Science and Technology, China. Her research is focused on network security.

Ying Lou
got his PhD degree in computer science from Northwestern Polytechnical University, in 2011, on web service and security. He\'s Associate Professor in Computer Science at Electronic & Information Engineering College of Henan University of Science and Technology, China. His main research interests include information service, intelligent information processing, etc.

Ruijuan Zheng
got her PhD degree in computer science from Harbin Engineering University, in 2008, on autonomic system security. She\'s Associate Professor in Computer Science at Electronic & Information Engineering College of Henan University of Science and Technology, China. Her main research interests include computer system security, network security, etc.


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