Advanced Network Management-spring2016


May 28th: materials for week 15-16 updated

May 22nd: papers/slides for Week 14 updated



General Information

Course Number


Class Time

9:50am-12:15pm Wednesday


Six-Jiao 6B-410

Project task deadlines

Project 1: Analyzing Search Logs in Practice 

  • task1: 03/23 11:59pm
  • task2: 04/06 11:59pm
  • task3: 04/27 11:59pm

Project 2: Investigating Factors that affect WiFi Latency

  • task1: 05/11 11:59pm
  • task2: 05/18 11:59pm
  • task3: 06/01 11:59pm 



Associate Professor

Department of Computer Science and Technology

Tsinghua University, Beijing, China 10084


Office: East Main Building 9-319

Mail: [email protected]

  • Project 1 mentor: Dapeng Liu liudp10(at)mails(dot)tsinghua(dot)edu(dot)cn






Course Description

Course Number


Required text

Reference texts
Computer Networking: Top-Down Approach (6th Edition)
by James F. Kurose, Keith W. Ross.
Statistical Data Mining Tutorials
by Andrew Moore.

You are expected to be familiar with at least one programming language. You should have taken an undergraduate Computer Networks or related course.

Attendence: 20%; Project 1:40%; Project 2: 40%
Each project has a mentor, and each student finishes each project by himself or herself.



This course is a graduate course and is primarily project-oriented. It aims to teach students how to build REAL systems that measure the REAL data from the networks and services, process the using Big Data techniques such as Machine Learning, and solve their REAL performance and security problems.

Through case studies based on recent research papers in top network conferences, this course will cover the latest research progress in network management in these areas: measurement, anomaly detection, diagnosis, and mitigation. Along the way, we will also briefly review techniques that have broader applications more than just network management, such as time series analysis, association rule mining, and machine learning.

This course focuses on how to improve the performance of Mobile Internet:

  • Targeted Services: Web-based Services such as search engine, online shopping and social networking; Video Streaming Services.
  • Targeted Networks: Enterprise WiFi Network, Residential WiFi & Broadband Networks, Cellular Networks, and Data Center Networks.
  • Targeted Devices: Smart Phones.



Week Date Topic, Papers, Slides and Reading List
1 Feb 24 Course Introduction & Network Basics
2 Mar 2 Web-based services (1)
3 Mar 9 Web-based services (2)
4 Mar 16 Web-based services (3)
5 Mar 23 Anomaly detection
6 Mar 30 Video streaming (1)
7 Apr 6 Video streaming (2)
8 Apr 13 No Class. Read Smart phone reading list
9 Apr 20 Smart phone
10 Apr 27 WiFi
11 May 4 No Class. Tsinghua Holiday
12 May 11 Anomaly localization
13 May 18 Dependency Discovery
14 May 25 Root Cause Analysis
15 Jun 1 Big Data Analytics System (1)
16 Jun 8 Big Data Analytics System (2)


Previous Course

Related Links

  • Conferences

Computer Science Conference Search    SIGCOMM     MobiCom  IMC     CoNEXT     NSDI

Mobiles    SIGKDD   OSDI   USENIX Security   UbiComp  WWW  INFOCOM VLDB

  • Statistics and Machine Learning Tools 

Wikipedia     R     WEKA     Scikit-learn        Correlation Tests     Matlab  SPSS

  • Public Resources

Deep Learning Resources

Longman Dictionary of American English

Time Series Analysis: Forecasting and Control (4th Edition) by George E. P. Box, Gwilym M. Jenkins, Gregory C. Reinsel.

Big Data Systems course materials by Professor Zhi Wang

               Spark Summit 


Internet Measurement Data Catalog

Internet Video@CMU

  • On reading and writting papers

Using tenses in scientific writing

Efficient Reading of Papers in Science and Technology

The Elements of Style

Style: Lessons in Clarity and Grace

How to Write and Publish a Scientific Paper

How to read a paper

              Common Bugs in Writing

  • Research Advice

How to Have a Bad Career in Research/Academia

Sound Measurement

Thinking Outside the Box

How to do great research

How to Increase the Chances Your Paper is Accepted at ACM SIGCOMM

做”接地气的”高水平的高水平科研 (by Dan Pei)





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