文献类型：期刊文献

英文题名：Modelling and Analysis of Regional Service Behavior Properties of Mobile Internet Applications

作者：Li, Ke[1];Xu, Xiaolong[1];Swamy, M. N. S.[2]

第一作者：李克

通讯作者：Li, K[1]

机构：[1]Beijing Union Univ, Coll Informat Technol, Beijing 100101, Peoples R China;[2]Concordia Univ, Dept Elect & Comp Engn, Montreal, PQ H3G 1M8, Canada

第一机构：北京联合大学智慧城市学院

通讯机构：[1]corresponding author), Beijing Union Univ, Coll Informat Technol, Beijing 100101, Peoples R China.|[1141734]北京联合大学智慧城市学院;[11417]北京联合大学;

年份：2017

卷号：5

起止页码：4795-4807

外文期刊名：IEEE ACCESS

收录：;EI(收录号：20171903659693);Scopus(收录号：2-s2.0-85019101252);WOS:【SCI-EXPANDED(收录号:WOS:000402940400093)】；

基金：This work was supported in part by the Key Laboratory of Universal Wireless Communications, Ministry of Education, Beijing University of Posts and Telecommunications, China, under Grant KFKT-2016102, in part by the National Natural Science Foundation of China under Grant 61372088, in part by the Funding Project for Academic Human Resources Development in Beijing Union University under Grant Rk100201510, and in part by the Huawei Innovation Research Program under Grant YB2014050020.

语种：英文

外文关键词：Traffic model; mobile Internet application; service behavior; crowd sourcing

摘要：In view of the facts that traditional traffic models are less effective in describing the new mobile internet applications and that the mobile user service behavior among regions with different levels of economic development are always different, a new modeling methodology of user service behavior specifically for mobile internet applications is proposed in this paper. Based on the crowdsourcing measurement data of the service behavior collected through massive end users in live mobile networks of China, the properties of three typical mobile internet services in three typical geographical regions are analyzed and compared with each other, by utilizing the proposed modeling methodology. And the relationships between some key properties of service behavior are analyzed with the maximal information coefficient method and the Pearson correlation coefficient method. The key parameters, differences, and internal relations among these services in typical geological regions of China are then identified. It provides a solid foundation for wireless product design, network planning, and optimization of mobile Internet services-oriented networks specifically in China, and is also a valuable reference for other countries of the similar situation.