基于数据挖掘的校园流量监测系统设计

Design of campus traffic monitoring system based on data mining

针对校园网网络覆盖面不广、执行功能相对单一、安全隐患较大的问题,提出以数据挖掘为基础,以K-means算法作为主要分析算法的校园流量监测系统。校园流量监测系统在原有的校园网管理系统上做了更为完善的改进与优化,能够随时随地监测校园网流量的异常与否,同时对校园网系统的数据信息进行收集,以分析其数据信息趋势并做出决策。通过实验对比可知,以数据挖掘为基础依据的校园流量监测系统比以往校园网系统更具多样性,系统稳定性更高,应用范围更加广泛,通过校园网系统对校园网络进行管理具有更好的执行能力。

In view that the coverage of campus network is not wide,the executive function is relatively single and the security risks are large,a data mining based campus traffic monitoring system which takes K⁃means algorithm as the main analysis algorithm is proposed.The campus traffic monitoring system is improved and perfected on the basis of the original campus network management system,so it can monitor the campus network traffic at anytime and anywhere.At the same time,the data information of the campus network system is collected to analyze the trend of data information and make decisions.In comparison with the previous campus network system,the campus traffic monitoring system based on data mining has more diversity,higher system stability and wider application range.Moreover,the campus network system has better executive ability in the management of the campus network.