基于用户行为大数据的广电宽带网络调优

Radio and TV Broadband Networks Optimization Based on Big Data of User Behavior

当前广电行业在互联网资源建设方面虽已初具规模,但相较于传统运营商而言仍有一定差距,因此本文提出充分结合广电自身宽带网络资源特点,依据网内互联网宽带用户的大数据行为分析,综合支撑引导网络出口及内网资源系统建设,以此来提升内网流量服务占比,有效降低出口系统及运维成本,同时也间接提升了用户体验。结合流量资源精细化分析,也为网络精准运营提供了有效保障。

Although radio and television industry has begun to take shape in terms of Internet resource construction, it still has a certain gap compared with traditional operators. Therefore, this paper proposes to fully combine the characteristics of radio and television’s own broadband network resources, based on big data analysis of Internet broadband users in network behavior, and comprehensively support and guide network export and internal network resource system construction, so as to increase the proportion of intranet traffic services, effectively reduce export system and operation and maintenance costs, and indirectly improve user experience. Combined with refined analysis of traffic resources, it also provides effective guarantee for accurate network operation.