Course pages 2012–13
Data Centric Networking
This module provides an introduction to data-centric networking, where data is a communication token for networking which impacts the computer system's architecture through a large volume of data processing. Integration of complex data processing with networking is a key vision for future computing systems. This course provides various aspects of data-centric networking ranging from content-based routing, data-flow parallel computing (e.g. MapReduce), to large graph structured data processing.
The module consists of 8 sessions, with 5 sessions on specific aspects of data-centric networking research. Each session discusses 2-3 papers, led by the assigned students. Each student will present about 2 paper reviews during the course. The 3rd session is hands-on tutorial session on MapReduce using data flow programming with Amazon EC2. The 1st session advises on how to read/review a paper together with a brief introduction of different perspectives in data-centric networking. The last session is dedicated to the presentation of the open-source project studies presented by the students. Two guest lectures are planned, covering inspiring current research on data-centric networking.
- Introduction to Data-Centric networking
- Data centric networking from different perspectives
- Content-Centric Networking (CCN) and Content Distribution Networks (CDN)
- Content-based routing
- Content distribution overlay
- Naming - Content represents network identifier
- Caching – Network as a storage
- MapReduce Tutorial
- Hands-on tutorial session of MapReduce parallel computing using CIEL/Skywriting data flow programming
- Programming in Data Centric Environment
- Network meets data flow programming
- Parallel data processing (e.g. Map/Reduce, Dryad/LINQ, CIEL)
- Declarative networking (e.g. P2, Declarative Sensor Network)
- Stream data processing and data/query model
- Stream data processing and continuous query processing
- Advanced data processing in networks (e.g. data model)
- Big Graphs Data Processing
- Graph Specific Data Parallel Programming
- Graphs for the storage and querying of data – graph database
- Distributed parallel query/storage platform for graph data
- Network holds data in delay tolerant networks
- Delay tolerant data
- Networked storage
- Opportunistic networking
- Presentation of Open Source project study
On completion of this module, students should:
- understand key concepts of data centric approaches in future networking and systems;
- obtain a clear understanding of building distributed systems using data centric programming and communication.
The reading club will involve 1 to 3 papers every week. At each session, around 3 papers are selected under the given topic, and the students present their review work.
The following three reports are required, which could be extended from the assignment of the reading club or a different one within the scope of data centric networking.
- Review report on a full length of paper (max 1800 words)
- Describe the contribution of the paper in depth with criticisms
- Crystallise the significant novelty in contrast to other related work
- Suggestions for future work
- Survey report on sub-topic in data centric networking (max 2000 words)
- Pick up to 5 papers as core papers in the survey scope
- Read the above and expand reading through related work
- Comprehend the view and finish an own survey paper
- Project study and exploration of a prototype (max 2500 words)
- What is the significance of the project in the research domain?
- Compare with similar and succeeding projects
- Demonstrate the project by exploring its prototype
The reports 1 and 2 should be handed in by the end of 5th week and 7th week of the course (not in any particular order). The report 3 should be handed in by the end of the Lent term.
The final grade for the course will be provided as a percentage and the assessment will consist of two parts:
- 25%: for reading club (participation)
- 75%: for the three reports
- 20%: Intensive review report
- 25%: Survey report
- 30%: Project study
 Malewicz, G., Austern, M., Bik, A., Dehnert, J., Horn, I., Leiser, N. & G. Czajkowski (2010) Pregel: A System for Large-Scale Graph Processing, SIGMOD, 2010.
 Jacobson, V., Smetters, D.K., Thornton, J.D., Plass, M.F., Briggs, N.H., & R.L. Braynard (2009) Networking named content, CoNEXT, 2009.
Murray, D., Schwarzkopf, M., Smowton, C., Smith, S., Madhavapeddy, A., & Hand, S. (2010) Ciel: a universal execution engine for distributed data-flow computing, NSDI, 2010.
A complete list can be found on the course web page.
R202 Data Centric Networking cannot be taken in conjunction with L21 Interactive Formal Verification in 2012-13.