Research On Drive Force Detect And Heat Forecast Of Network Emergency

In recent years, network emergencies increased rapidly. Earlier prediction of scale and mastery of driving forces behind network emergency would largely benefit our response. Our major research focused on the following aspects.(1) Proposed a driving force detection method. We synthesized the following features: the latency heat, ID concentration, proportion of simple articles, ratios of newly registered IDs and geographical concentration of authors and calculated a composite index indicating the possibility and intensity of driving force.(2) Summarized the distribution of network emergency. Set up a"Browse-Reply"model to describe the network emergency, and found that heat distribution of natural emergency fitted combination of Poisson distribution functions. Network emergency with weak driving force still fitted Poisson distribution after removing the driving parts.(3) Proposed a prediction model and indexes. We proposed a prediction method based on heat distribution information. The method can predict the entire heat of the network emergency on early outbreak stage. Then we defined different indexes according to different requirements of network users and network regulators.For dependency of each part, we didn't put all the experiments at the end of the thesis. Instead, we put them separately on the end of each part to make it more comprehensible. We compared"Jia Junpeng event"and"Li Gang event"to verify the effectiveness of driving force detection method. We analyzed lots of network emergencies, verified that most of the emergencies fitted Poisson distribution and the prediction result was effective. Most of measurement errors were less than 50%.