DocumentCode :
3421536
Title :
A Service Self-Optimization Algorithm based on Autonomic Computing
Author :
Zheng, Ruijuan ; Zhang, MingChuan ; Wu, Qingtao ; Li, Guanfeng ; Wei, Wangyang
Author_Institution :
Electron. & Inf. Eng. Coll., Henan Univ. of Sci. & Technol., Luoyang, China
fYear :
2009
fDate :
17-19 Aug. 2009
Firstpage :
805
Lastpage :
808
Abstract :
Under the intrusion or abnormal attack, how to autonomously supply undergraded service to users is the ultimate goal of network security technology. Firstly, combined with martingale difference principle, a service self optimization algorithm based on autonomic computing-S2OAC is proposed. Secondly, according to the prior self optimizing knowledge and parameter information of inner environment, S2OAC searches the convergence trend of self optimizing function and executes the dynamic self optimization, aiming at minimum the optimization mode rate and maximum the service performance. Thirdly, set of the best optimization mode is updated and prediction model is renewed, which will implement the static self optimization and improve the accuracy of self optimization prediction. At last, the simulation results validate the efficiency and superiority of S2OAC.
Keywords :
optimisation; security of data; software fault tolerance; abnormal attack; autonomic computing; intrusion attack; network security technology; service self-optimization algorithm; static self optimization; Computational modeling; Computer networks; Computer security; Educational institutions; Grid computing; Predictive models; Read only memory; Reflection; Software architecture; Virtual reality;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Granular Computing, 2009, GRC '09. IEEE International Conference on
Conference_Location :
Nanchang
Print_ISBN :
978-1-4244-4830-2
Type :
conf
DOI :
10.1109/GRC.2009.5255010
Filename :
5255010
Link To Document :
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