Research on the deployment tactics of workloads confliction based on the neural network in cloud computing

Wu Qinlan, Huang Yanmei

COMPUTER MODELLING & NEW TECHNOLOGIES 2013 17(5B) 80-83

School of Internet of Things Engineering, Jiangxi College Of Engineering, JiangXi, 338029, China

Aiming at the degrading system performance that busty workloads bring in cloud computing, a resource deployment model based on error back-propagation neural network was proposed to resolve the problems referred to above. A network module is started automatically when the beginning of busty workloads is judged. The prediction of parameter adjustment value is carried out by using pertained network to achieve the purpose of tracking dynamically the changing of underlying resource and outside world task in cloud computing system. The results of simulation in CloudSim prove that the response speed of resource deployment can be improved efficiently by bringing neural network module.