移动业务特征认知及其分布模型:以即时消息为例

The characteristics study of mobile instantaneous messaging traffic in cellular network

众所周知,业务流量特点建模有助于设计能效低、稳定性强的网络协议.近年来新兴业务如雨后春笋一般涌现,重新考察这些新业务的特点也就至关重要了.本文以即时消息业务为例,了解当前移动互联网下的流量新特点.为了得到可信的结果,采集了大量的蜂窝网即时消息实测数据,并从用户层面和基站层面两个维度去研究其统计规律.首先在用户层面,通过用户级的数据包包长和到达间隔建模发现,相关结果同传统上包长符合几何分布、到达间隔满足指数分布的3GPP报告明显不同;与之相反,微信包长和到达间隔分别遵循幂律和对数正态分布.其次在基站层面,通过随机选取基站发现,α-稳定模型能更好地刻画基站层面基站流量——这一结果同传统固定宽带网络业务研究相吻合.最后,建立了用户层面数据包同基站层面流量的理论联系.

Understanding traffic characteristics plays a vital role in network protocol design, which aims to minimize network resource consumption and maximize network stability. In this paper, we use the example of the mobile instantaneous messaging （MIM） service in cellular networks and try to understand its traffic characteristics. Specifically, in order to reach credible conclusions, our research uses practical measurement records from the MIM services of China Mobile at two different levels. First, a dataset of individual message level （IML） traffic is examined and reveals power-law distributed message length and lognormal distributed inter-arrival time. The heavy-tailness of which completely diverts from the geometric and exponential models recommended by 3GPP. Second, another dataset is used to examine the statistical patterns of aggregated traffic within a base station, and demonstrates the accuracy of α-stable models for aggregated traffic. Furthermore, we verify that α-stable models are suitable for characterizing traffic in both conventional fixed core networks and cellular access networks. Finally, by using the generalized central limit theorem, we build a theoretical relationship between the distributions of IML traffic and aggregated traffic.