caa a22 4500 605468567 CHVBK 20210128100317.0 cr unu---uuuuu 210128e20150601xx s 000 0 eng 10.1007/s00500-014-1359-9 doi (NATIONALLICENCE)springer-10.1007/s00500-014-1359-9 Adaptive Web QoS controller based on online system identification using quantum-behaved particle swarm optimization [Elektronische Daten] [Wei Fang, Jun Sun, Xiaojun Wu, Vasile Palade] Web quality of service (QoS) control can effectively prevent a Web Server from becoming overloaded. This paper presents an adaptive controller for Web QoS, which dynamically adjusts parameters of the proportional-integral (PI) controller according to the changes of the Web server model. Different from the existing methods based on the off-line system identification, the adaptive Web QoS controller is implemented based on the online system identification through a quantum-behaved particle swarm optimization (QPSO) algorithm and a mutated version of QPSO (MuQPSO). The proposed approach for online system identification by QPSO and MuQPSO shows better performance than genetic algorithms and the particle swarm optimization algorithm on the simulation tests. Then, the performance of the adaptive controller for Web QoS is tested in three experiments and compared with that of fixed PI controller. Experimental results show that the adaptive control employing online system identification by QPSO and MuQPSO algorithms is able to control the Web server resource more effectively in case of overload and, thus, improves the Web QoS. Springer-Verlag Berlin Heidelberg, 2014 Particle swarm optimization nationallicence Quantum-behaved particle swarm optimization nationallicence Web QoS nationallicence Adaptive control nationallicence Fang Wei Key Laboratory of Advanced Control for Light Industry, Ministry of Education, Jiangnan University, 214122, Wuxi, China aut Sun Jun Key Laboratory of Advanced Control for Light Industry, Ministry of Education, Jiangnan University, 214122, Wuxi, China aut Wu Xiaojun Key Laboratory of Advanced Control for Light Industry, Ministry of Education, Jiangnan University, 214122, Wuxi, China aut Palade Vasile Department of Computing, Coventry University, Coventry, UK aut Soft Computing Springer Berlin Heidelberg 19/6(2015-06-01), 1715-1725 1432-7643 19:6<1715 2015 19 500 https://doi.org/10.1007/s00500-014-1359-9 text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s00500-014-1359-9 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Fang Wei Key Laboratory of Advanced Control for Light Industry, Ministry of Education, Jiangnan University, 214122, Wuxi, China aut NATIONALLICENCE 700 1- Sun Jun Key Laboratory of Advanced Control for Light Industry, Ministry of Education, Jiangnan University, 214122, Wuxi, China aut NATIONALLICENCE 700 1- Wu Xiaojun Key Laboratory of Advanced Control for Light Industry, Ministry of Education, Jiangnan University, 214122, Wuxi, China aut NATIONALLICENCE 700 1- Palade Vasile Department of Computing, Coventry University, Coventry, UK aut NATIONALLICENCE 773 0- Soft Computing Springer Berlin Heidelberg 19/6(2015-06-01), 1715-1725 1432-7643 19:6<1715 2015 19 500