一种基于在线辨识的Web服务自适应接纳控制

An adaptive admission control of Web service based on system model online identification

设计并实现了一种基于量子行为粒子群算法(QPSO)系统模型在线辨识的Web服务自适应接纳控制,根据系统模型的变化在线调节比例积分控制器参数.通过接纳时间比反馈控制机制,调整控制周期内服务器接纳请求的时间长度,进而实现接纳控制.通过仿真实验,并与多种不同控制方法进行比较,所得结果表明,在线辨识自适应控制能够在服务器过载的情况下更有效地控制系统资源,进一步提高了服务质量.

An adaptive admission control of Web service based on system model online identification using quantumbehaved particle swarm optimization（QPSO） is designed and implemented, which dynamically adjusts parameters of PI controller according to the changes of system model. In order to achieve admission control, a session-based admission timeratio feedback control mechanism is introduced, which manages the amount of requests that the server can accept during the control period. The simulation results of Apache Web server compared with several control methods show that the adaptive control based on online system identification is able to control the system resources of the server more effectually in case of overload and further improves the service quality.