The highly topological dynamics characterizes the most fundamental property of satellite networks with respect to terrestrial ones. The manifest feature directs the researches on various aspects of satellite networks, including protocol architecture investigations, routing protocol and reliable transmission control protocol design and enhancement, etc. This paper systematically quantifies the dynamical activities of regular low earth orbit (LEO) satellite network topologies. The number and length of network snapshots are formulated concisely. With this work, it compensates for the simplified topological assumptions in many LEO satellite network related researches. The thorough understanding of this basic feature not only provides for an accurate quantification of network behavior for researchers on satellite network community, but also could act as a guidance for future satellite constellation design and optimization.

The end-to-end delay of Internet is a fundamental indicator for network performance evaluation and has been becoming a hot issue in network measurements in recent years. There are two kinds of metrics related to the end-to-end latency, i.e., Round Trip Delay and One-way Delay metric. In the paper, we survey the recent progresses on these two types of metrics measurement. Special concerns are on the clock synchronization issue in one-way delay measurement. The problems in deploying end-to-end delay measurement and the timestamping issue are also summarized. The potential new research directions in delay measurement and analysis are discussed.

传统的基于应用层的网卡监测方式已难以对高速网卡活动信息进行实时、准确监测。为此，分析基于NDIS（network drivet interface specification）中间层驱动和Window8网络数据包过滤技术的特点，采用核心态NDIS中间层驱动程序实现了与底层网络接口设备具体细节无关的高速网络设备监测技术，设计并实现了windows平台下基于NDIS的网卡监测器。它分为应用层和驱动层两个模块，能够在保证高性能的情况下在数据链路层同时对多个网卡进行精确监测，其主要特点是对所有数据包的分析处理都在核心态进行。

具有星际链路的双层通信星座网络可为全球提供宽带实时多媒体通信服务，路由算法设计是其中关键技术之一。本文详细介绍了由低轨卫星与中轨卫星构成的空间信息通信网双层星座系统体系结构，提出了一种新的具有QoS保证的双层卫星网络路由算法。仿真结果表明提出的路由算法可以满足系统的QoS业务要求的延迟、丢包率与抖动等指标。

The long-tailed distribution characterizes many properties of Internet traffic. The property is often modeled by Lognormal distribution, Weibull or Pareto distribution theoretically. However, it hinders us in traffic analysis and evaluation studies directly from these models due to their complex representations and theoretical properties. This paper proposes a Hyper-Erlang Model (Mixed Erlang distribution) for such long-tailed network traffic approximation. It fits network traffic with long-tailed characteristic into a mixed Erlang distribution directly to facilitate our further analysis. Compared with the well-known hyperexponential based method, the mixed Erlang model is more accurate in fitting the tail behavior and also computationally efficient.