Zhang Honggang

The characteristics study of mobile instantaneous messaging traffic in cellular network

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

Energy efficiency of soft real time service in hyper-cellular network with users' behavior prediction

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Method for detecting sparse event of wireless sensor network by loop restructuring

-stable models for aggregated traffic. Furthermore, we verify that

Cellular network traffic prediction method based on space-time compression perception

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Method for realizing distributed Luby transform (LT) codes on the basis of layering network topology

-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.

SDN based management method of 802.11 wireless access network

Many users require the same content, such as breaking news, newly released movies, and favorites videos. The same content is transmitted multiple times across wireless cellular network because current wireless network is designed to transmit data based on user requests, which exhausts wireless bandwidth and incurs high energy costs. This paper presents a soft real time service frame that is user-centric and content-aware. The frame broadcasts popular content to user equipment before users ask for it to achieve higher network energy efficiency and enhance quality of service. We propose a popularity prediction scheme, a target user group prediction scheme, a dynamic broadcast area calculation scheme, and a content pushing scheme. We build a system model to analyze key parameters in the service framework. As shown in simulations, the wireless network energy efficiency is improved 2 times with news contents in public cellular scenarios, and is improved 50 times with online study contents in campus cellular scenarios.