Abstract: With the growing popularity of cloud computing,more and more users choose to migrate their business to the cloud computing system.Users’ usage habits and social routine working laws swarm into the cloud computing system along with the influx of large numbers of users,such as applying intensively to cloud computer system for resource nodes as early as 8:00,which leads into a kind of predictable resources conflict.In view of the problems above,a resource deployment model based on active prediction was proposed.Firstly,the task request amounts of next cycle are predicted according to the algorithm cycle length of Holt-Winters seasonal exponential smoothing model in prediction model,and determination of whether to make response to the current task request amounts or not and the specific amount,location and other parameter indicators should be made according to the active prediction algorithm designed to achieve active response capabilities to users’ usage patterns.The simulation experiment was conducted using CloudSim,and the performance of model proposed was judged systematically.Experimental results show that AF-HW model can effectively enhance the single-point and overall response rate when responding to predictable massive and concurrent task requests,so that users can get a better experience.

Key words: Cloud computing,Predictive,Resource allocation,Holt-Winters model,Systems optimize