Analysis Of Teaffice And User Behavior Of Mobile Internet Games

With the rapid development of mobile internet,APP runs on all types of mobile smart devices is also booming,and penetrate deep into people's lives.Since the country opened 3G network services,intelligent terminals is spreading rapidly.The China Internet Development Statistics Report released by China Internet Network Information Center(CNNIC)on July 23,2015 shows that internet users gradually access the network from the the phone side other than computer migration.In 2012,the smart phone shipments of China has become the largest around the world.As the main carrier of user-generated internet traffic,development of the access device will change the user's online behavior.APP running on the mobile intelligent terminal as a final mobile internet traffic generator,analyzing its traffic characteristics and extracting the user behavior information is important to grasp the the development of mobile internet and specific category.This thesis describes the development of mobile online games,including identification method for mobile internet game traffic and user behavior analysis.We also describes the tools used for analysis--Hadoop distributed storage and computing framework.Introduced the Hadoop-based distributed Big-Data analysis services of our laboratory,including automated installation and configuration of the cluster and the related optimization in order to improve the service quality and stability made.In order to analyze a wide range and a huge number of mobile Internet game more quickly and efficiently,we developed the APP automatically download system and traffic characteristics extraction system.In order to identify game data from the mass of existing Internet network traffic quickly for data preprocessing.Meanwhile,in order to fast mobile Internet user behavior analysis more quickly,we developed mobile Internet gaming information extraction system based on MapReduce framework.Based on basic data extracted from the traffic data,we analyzed users daily participation number,landing time,the account number for different types of mobile Internet online games.At the same time,for different types of games,we also analyzed the distribution of the account type,version,distribution,distribution login server.