It should be mentioned that this course is NOT about specific applications.
Also, the course is NOT structured around certain standardized
application-layer protocols, such as HTTP, RTP, or SIP. We will discuss
some of these protocols in the context of the applications that use them.
Lectures and student presentations
The course will cover 12 topics, listed below.
Each topic corresponds roughly to one week of the semester.
There will be two (in some cases, three) class sessions for each topic.
In the first session of each topic, the instructor will cover the fundamentals, providing
the necessary background to understand that topic.
In the second session, we will learn and discuss about important and recent research
results in that area. These research papers will be presented by the
students. Each student will present one or two papers during the semester.
The presentation of a research paper should take about 15 minutes, with 5 minutes for
questions (asked both by the instructor and other students).
The presenter needs to send the slides (ppt or pdf) to the instructor at least two
days before the presentation; the instructor may ask for changes.
All presentation slides will be posted online at this webpage.
Prerequisites
Some (recent and solid) knowledge of computer networking
is required. This should certainly NOT be the first networking course
you are
taking. However, you do not need to be a "networking student" to
take this course. Students with a primary interest in machine learning
or AI, HCI, or databases will also find some of the topics interesting.
CS6250 is NOT a required prerequisite for this course, as long as you
have taken another networking course before.
Textbook references
The course will not use a textbook. Instead, we will study a number
of research and survey papers (listed in the syllabus section).
You are strongly encouraged to look at the recent proceedings of the
following conferences, especially as you look for a project topic:
- World Wide Web (WWW) conference
- Networks and Operating Systems Support for Digital Audio and Video (NOSSDAV)
- Internet Measurement Conference (IMC)
- Sigcomm Conference on Online Social Networks (COSN)
- International AAAI Conference on Weblogs and Social Media (ICWSM)
- ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD)
You may also find the following textbooks useful at certain
parts of the course.
- "Web Protocols and Practice", by B.Krishnamurthy and J.Rexford.
- "Networks, Crowds and Markets", by D.Easley and J.Kleinberg.
- "Digital Compression for Multimedia", by Gibson et al.
- "Internet Measurement", by M.Crovella and B.Krishnamurthy.
- "Web Data Mining", by B.Liu.
Syllabus (links to lecture slides are available on T-Square)
-
Introduction: Course overview, Examples of course projects
-
Topic-1: Packet voice
References:
- The first 6 sections of : VoIP: A comprehensive survey on a promising technology by S.Karapantazis and F-N.Pavlidou.
- A Survey of Packet Loss Recovery Techniques for Streaming Audio by C. Perkins et al.
- Detailed analysis of Skype traffic by D. Bonfiglio et al.
- Adaptive Playout Scheduling and Loss Concealment for Voice Communication Over IP Networks by Y.J. Liang et al.
- Optional: How NAT-compatible are VoIP Applications? by Y-D. Lin et al.
- Optional: A
comprehensive survey of voice over IP security research by A. Keromytis.
-
Topic-2: Packet video - the basics
References:
- Video compression tutorial by H-H. Chen
- Video Compression: From Concepts to the H.264/AVC Standard by G. Sullivan et al.
- Adaptation of Audiovisual Contents and Their Delivery Means by M. T. Diallo et al.
- A Longitudinal View of HTTP Video Streaming Performance by L. Plissonneau and E. Biersack
- An Experimental Evaluation of Rate-Adaptation Algorithms in Adaptive Streaming over HTTP by S. Akhshabi et al.
- Optional: Watching video over the Web (Part 1 only) by A. Begen et al.
- Optional: Dynamic Adaptive Streaming over HTTP – Standards and Design Principles by T. Stockhammer
-
Topic-3: Packet video - the state of the art
References:
- Server-Based Traffic Shaping for Stabilizing Oscillating Adaptive Streaming Players by S. Akhshabi et al.
- Unreeling Netflix: Understanding and Improving Multi-CDN Movie Delivery by V. Kumar Adhikari et al.
- YouTube Everywhere: Impact of Device and Infrastructure Synergies on User Experience by A. Finamore et al.
- A Buffer-Based Approach to Rate Adaptation: Evidence from a Large Video Streaming Service by T-Y.Huang et al.
- Developing a Predictive Model of Quality of Experience for Internet Video by A.Balachandran et al.
- Improving Fairness, Efficiency, and Stability in HTTP-based Adaptive Video Streaming with FESTIVE by J. Jang et al.
- Optional: An Experimental Investigation of the Akamai Adaptive Video Streaming by L. De Cicco and S. Mascolo
-
Topic-4: Peer-to-peer applications
References:
- A survey and comparison of peer-to-peer overlay network schemes by EK.Lua et al.
- Chord: A scalable peer-to-peer lookup service for internet applications by I.Stoica et al.
- Understanding churn in peer-to-peer networks by D.Stutzbach and R.Rejaie
- Challenges, Design and Analysis of a Large-scale P2P VoD System by Y. Huang et al.
- Low-resource routing attacks against TOR by K.Bauer et al.
- Optional: Search and Replication in Unstructured Peer-to-Peer Networks by Q.Lv et al.
-
Topic-5: Multiplayer games and virtual worlds
References:
- Donnybrook: Enabling Large-Scale, High-Speed, Peer-to-Peer Games by A. Bharambe et al.
- Colyseus: A Distributed Architecture for Online Multiplayer Games by A.Bharambe et al.
- Comparing Interest Management Algorithms for Massively Multiplayer Games by J-S. Boulanger et al.
- A Peer Auditing Scheme for Cheat Elimination in MMOGs by J.Goodman and C.Verbrugge
- Is there life in Second Life? by M.Varvello et al.
- Optional: Bandwidth requirement and state consistency in three multiplayer game architectures by J.Pellegrino and C.Dovrolis
-
Topic-6: Overview of network analysis methods
References:
- Complex Networks: Structure and Dynamics by S. Boccaletti et al. (you can focus on the parts covered in the lecture)
- Community detection in graphs by S.Fortunato (this is a very long survey. You can use it mostly as reference, focusing on the methods we will discuss in class)
-
Topic-7: Social
networking applications
References:
- What is Twitter, a Social Network or a News Media? by H. Kwak et al.
- The Anatomy of the Facebook Social Graph by J.Ugander et al.
- On the evolution of user interaction in Facebook by B.Viswanath et al.
- Optional: Co-evolutionary dynamics in social networks: A case study of Twitter by D.Antoniades and C.Dovrolis
-
Topic-8: Information diffusion over the Web
References:
- The role of social networks in information diffusion by E. Bakshy et al.
- Comparison of online social relations in volume vs interaction: a case study of cyworld by Chun et al.
- Cost-effective Outbreak Detection in Networks by J.Leskovec et al.
- Optional: Behavioral Profiles for Advanced Email Features by Karagiannis and Bojnovic
-
Topic-9: The Web as a marketplace and a public forum
References:
- The role of social networks in online shopping: information passing, price of trust, and consumer choice by S.Guo et al.
- Governance in Social Media: A case study of the Wikipedia promotion process by J.Leskovec et al.
- Optional: Meme-tracker and the dynamics of the news cycle by J.Leskovec et al.
-
Topic-10: Searching the Web
References:
- Searching the Web by Arasu et al. (focus on PageRank - section 5.1)
- Topical interests and the mitigation of search engine bias by S.Fortunato et al.
- Detecting influenza epidemics using search engine query data by J.Ginsberg et al.
- Optional: Spatial variation in search engine queries by L.Backstrom et al.
-
Topic-11: Recommendation engines and their effect
References:
- Towards the Next Generation of Recommender Systems: A Survey of the State-of-the-Art and Possible Extensions by G.Adomavicius and A.Tuzhilin (focus on the first two sections)
- Amazon. com recommendations: Item-to-item collaborative filtering by G.Linden et al.
- Experimental study of inequality and unpredictability in an artificial cultural market by M.Salganik et al.
- Optional: Large-Scale Parallel Collaborative Filtering for the Netflix Prize by Y.Zhou et al.
-
Topic-12: Collective intelligence
References:
- An experimental study of the coloring problem on human subject networks by M.Kearns et al.
- Collaborative learning in networks by W.Mason and D.Watts
- Predicting protein structures with a multiplayer online game by S.Cooper et al.
- Earthquake Shakes Twitter Users: Real-time Event Detection by Social Sensors by Sasaki et al.
Term Project
Students will work on a term project in groups of
two or three students (three is preferred).
The term project should hopefully be the most creative and fun part
of the course. The project will be a "hands-on" study
that is related to one or more Internet applications. The
exact project description will be determined by
students themselves. The only requirement is that the project should
have a sufficiently challenging component, and it should be relevant to
the syllabus of this course.
For instance, you can write a new (or modify
an existing open-source) application that is related to the course
topics. You can measure or experiment with existing applications,
evaluating their performance or other characteristics. You can study
the social network of an online community application. Or, you can
propose, study and implement an algorithm that would be useful in one
of the applications we cover (for example, an advanced web searching
algorithm based on clustering or semantic associations). Writing a
survey paper or just running some applications would certainly not be enough.
Project Milestones:
- Asap: form groups of 3 students - email group name, participants
(names and email addresses) to the TA and instructor
- Feb-6: submit a 2-page project description, explaining what you want to do and how you plan to do it.
The instructor and TA will provide feedback and you may need to revise your project
description.
- Mar-4: progress report -- each group will present in class what has been
accomplished so far. Last opportunity to modify the project's scope.
- Apr 24: project presentations.
Grading
- Midterm exam:
20%
- Final exam:
20%
- Presentation of a research paper:
10%
- Homeworks:
10%
- Term project and final presentation: 40%
Professional education students (distance learning)
The key difference is that you will do the course project individually. Consequently, your project's scope and level of difficulty should be set accordingly, in collaboration with the TA/instructor.
You will also need to present a research paper and your final project. The presentations can be done live through skype or they can be pre-recorded.
Everything else will be the same with the main course section.
If you have any additional questions, please do not hesitate to email the instructor.