Association rules mining analysis of app usage based on mobile traffic flow data

With the rapid development of mobile Internet, more and more Apps emerge in people's daily life. It is important to analyze the relations among Apps, which is helpful for network management and control. In this paper, we utilize network footprint data which consists of DPI data from ISPs and Crawler data from Web for App usage analysis. Focusing on the most popular Apps in China, we propose a distributed NFP data collection and processing framework. We do association rules mining on NFP data by using Apriori and MS-Apriori algorithm. Experimental results validate our proposed method and present some interesting association rules of Apps.