应电信学院管晓宏教授邀请，计算机网络领域著名专家Don Towsley教授和邱达民教授来我校访问并进行学术报告。Don Towsley教授, 计算机网络领域顶级期刊IEEE/ACM Transaction on Networking(TON)的前任主编，现为美国University of Massachusetts教授,IEEE/ACM Fellow。邱达民教授毕业于伦敦帝国大学和哈佛大学，现为香港中文大学信息工程系主任，IEEE Fellow。

报告时间：周二（2009-11-17日）上午9:00~12:00

地点：科学馆207

报告一：Towards a Network Measurement Science

报告人：Prof. Don Towsley

Abstract

Network measurements these days are conducted in a mostly ad hoc manner.

Users quite often perform one-time measurement experiments in an unprincipled approach, in many case leading to inefficient measurements and, even worse, biased measurements. Vendors have developed and standardized a number of measurement tools, e.g., NetFlow from Cisco.

However, these tools are typically inefficient in that they often yield statistics with large error ranges.

In this talk we argue for the need for a network measurement science that can deal in a principled way with the issues of measurement efficiency and measurement bias. To deal with measurement efficiency, we advocate the use of Fisher information during the design of measurement experiments and measurement tools. Briefly, Fisher information is a measure of the anount of information that a single measurement provides to the computation of a statistic such as loss rate. We illustrate its application to the problem of estimating flow size distribution based on packet sampling as found in NetFlow. In the context of measurement bias, we shift our attention to measurements leading to the characterization of graphs as commonly found in the Internet and on-line social networks. We review several flawed studies where the measurements were biased and then describe how measurements based on random walks through graphs can be used to remedy these deficiencies.

报告二: "Publish or perish" in the Internet Age

报告人：Prof Dah Ming Chiu (邱达民)

Abstract

In some academic communities, such as the computer networking field, the rate of publication is increasing drastically. We are interested in studying the publication system to see how to make it scale and become more helpful for researchers and others who use the system (e.g. for evaluation).

As a first step, we recently did some analysis of a paper database derived from a selected set of computer networking conferences and journals spanning the past twenty years (1989-2008). Instead of producing the citation statistics ourselves based on a subset of papers, we relied on citation count given by Google Scholar. We are able to compare the publication venues we selected using different metrics. We considered the effect of increasing publication rate on the comparison of citation counts. We also study the relationship between number of authors, papers published, publication per author, and #authors per publication, and show the trend over the years we studied.

欢迎感兴趣的老师和同学们前来参加！