Computer Laboratory

Data Centric Systems and Networking (2013-2014 Lent Term)

DCSN - R212

Additional References

review_log

Open Source Projects

Reading Club Papers

Contact

 

 

 

 

 

 

 

  

 

Overview

This module provides an introduction to data centric systems and networking where data is a communication token in networking and its impact on the computer system's architecture. Large-scale distributed applications with big data processing will grow ever more in importance and become a pervasive aspect of the lives of millions of users. Supporting the design and implementation of robust, secure, and heterogeneous large-scale distributed systems is essential.   This course provides various perspectives on data centric systems and networking, including content-based routing, data-flow programming, stream processing, and large-scale graph data processing, thus providing a solid basis to work on the next generation of communication paradigms and system design. On completion of this module, the 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 approach

Module Structure

The module consists of 8 sessions, of which 6 sessions focus on a specific aspect of the topic in data centric networking and systems research. Each session discusses 2-3 papers, led by the assigned students. Each student will present about 2 paper reviews during the course. The first session advises how to read/review a paper and a brief introduction of different perspectives in data centric networking. The last session is dedicated to the presentation of the open source project studies present by the students. One hands-on session on data-flow programing and one guest lectures are planned (subject to change), covering inspiring current research in the data centric networking and systems domain.

Schedule and Reading List

We’ll meet in SW01 every Tuesday (from January 21 to March 11) in 2014. The time slot is 9:00-11:00 on Tuesday except February 18 and 25.

 2014/01/21 Session 1: Introduction to Data Centric Systems and Networking

  • Introduction to Data Centric Systems and Networking (slides)
  • Assignment details
  • Guidance of how to read/review/present a paper
  • Technologies for Big Data Processing (slides)
  • Guidance to Open Source Project

 2014/01/28 Session 2: Programming in Data Centric Environment

  • Data flow programming

Ilias Giechaskiel (slides)

1. Yuan Yu, Michael Isard, D. Fetterly, M. Budiu, U. Erlingsson, P.K. Gunda, J. Currey: DryadLINQ: A System for General-Purpose Distributed Data-Parallel Computing Using a High-Level Language, OSDI, 2008.

2.1. Boon Thau Loo, Tyson Condie, Joseph M. Hellerstein, Petros Maniatis, Timothy Roscoe, and Ion Stoica: Implementing Declarative Overlays, SOSP, 2005.
2.2. Boon Thau Loo, Tyson Condie, Minos Garofalakis, David E. Gay, Joseph M. Hellerstein, Petros Maniatis, Raghu Ramakrishnan, Timothy Roscoe, Ion Stoica: Declarative Networking, Communications of the ACM, Vol. 52 No. 11, pp. 87-95, 2009.

3. Peter Alvaro, Tyson Condie, Neil Conway, Khaled Elmeleegy, Joseph M. Hellerstein, Russell Sears: Boom analytics: exploring data-centric, declarative programming for the cloud, Eurosys 2010.

4. J. Dean, S. Ghemawat: MapReduce: Simplified Data Processing on Large Clusters, OSDI, 2004.

Niko Stahl (slides)

5. Derek Murray, Malte Schwarzkopf, Christopher Smowton, Steven Smith, Anil Madhavapeddy and Steven Hand: Ciel: a universal execution engine for distributed data-flow computing, NSDI 2011. 

Frank McSherry's Talk on Differential Dataflow is here. Naiad Twitter Demo is here.

Karthik Nilakant (slides) Derek's talk of Naiad.

6.1. Frank McSherry, Rebecca Isaacs, Michael Isard, and Derek G. Murray, Composable Incremental and Iterative Data-Parallel Computation with Naiad, no. MSR-TR-2012-105, 2012. 

6.2. D. Murray, F. McSherry, R. Isaacs, M. Isard, P. Barham, M. Abadi: Naiad: A Timely Dataflow System, SOSP, 2013. 

Gustaf Helgesson(slides)

7. P. Bhatotia, A. Wieder, R. Rodrigues, U. A. Acar, and R. Pasquini: Incoop: MapReduce for incremental computation, ACM SOCC, 2011.

8. Dionysios Logothetis, Christopher Olston, Benjamin Reed, Kevin Webb and Kenneth Yocum: Stateful Bulk Processing for Incremental Analytics, SOCC, 2010.

 2014/02/04 Session 3: Processing Models of Large-Scale Graph Data

  • Scalable distributed processing of graph structured data, processing model, and programming model
  • Apatch Giraph demo

1. J. Pujol, V. Erramilli, G. Siganos, X. Yang, N. Laoutaris, P. Chhabra, P. Rodriguez: The Little Engine(s) That Could: Scaling Online Social Networks, SIGCOMM, 2010.

Valentin Dalibard (slides)

2. G. Malewicz, M. Austern, A. Bik, J. Dehnert, I. Horn, N. Leiser, and G. Czajkowski: Pregel: A System for Large-Scale Graph Processing, SIGMOD, 2010.

3. U. Kang, C. E. Tsourakakis, C. Faloutsos: PEGASUS: A peta-scale graph mining system - Implementation
and observations
, ICDM , 2009.

Haikal Pribadi (slides)

4. Z. Qian, X. Chen, N. Kang, M. Chen, Y. Yu, T. Moscibroda, Z.Zhang: MadLINQ: large-scale distributed matrix computation for the cloud, EuroSys, 2012.

Will Sewell (slides)

5. S. Hong, H. Chafi, E. Sedlar, K.Olukotun: Green-Marl: A DSL for Easy and Efficient Graph Analysis, ASPLOS, 2012.

6. Dimitrios Prountzos Roman Manevich Keshav Pingali: Elixir: A System for Synthesizing Concurrent Graph Programs, OOPSLA, 2012.

7. D. Nguyen, A. Lenharth, K. Pingali: A Lightweight Infrastructure for Graph Analytics, SOSP 2013.

Gustaf Helgesson (slides)

8. J. E. Gonzalez, Y. Low, H. Gu, D. Bickson, and C. Guestrin: Powergraph: distributed graph-parallel computation on natural
graphs
. OSDI, 2012.

9. .J. Shun and G. Blelloch: Ligra: A Lightweight Graph Processing Framework for Shared Memory, PPoPP, 2013. 

 2014/02/11 Session 4: MapReduce Handson Tutorial with Amazon EC2  

  • MapReduce Tutorial: Hands-on tutorial session of MapReduce parallel computing using CIEL/Skywriting on data flow programming (Tutor: Karthik Nilakant).
  • Quick Introduction to Python.
  • If you want to work using your laptop (Linux), bring it with you!

 

 2014/02/21 Session 5: Graph Data Processing in Resource Limited Environment  

1. W. Han, S. Lee, K. Park, J. Lee, M. iKim, J. Kim, H. Yu: TurboGraph: A Fast Parallel Graph Engine Handling
Billion-scale Graphs in a Single PC
,
KDD, 2013.

Niko Stahl (slides)

2. A. Kyrola and G. Blelloch: Graphchi: Large-scale graph computation on just a PC, OSDI, 2012. 

3. A. Roy, I. Mihailovic, W. Zwaenepoel:   X-Stream: Edge-Centric Graph Processing using Streaming Partitions, SOSP, 2013.

lias Giechaskiel (slides)

4. X. Hu1, Y. Tao, C. Chung:  Massive Graph Triangulation, SIGMOD, 2013.

5. W. Xie, G. Wang, D.Bindel, A. Demers, J. Gehrke:  Fast Iterative Graph Computation with Block Updates, VLDB, 2014.

Will Sewell (slides)

6. J. Zhong, B. He:  Medusa: Simplified Graph Processing on GPUs, IEEE TPDS, 2013.

7. A. Gharaibeh, E. Santos-Neto, L. Costa, M. Ripeanu Efficient Large-Scale Graph Processing on Hybrid CPU and GPU Systems, IEEE TPC, 2014.

 2014/02/28 Session 6: Stream Data Processing and Data/Query Model 

1. V. Gulisano, R. Jimenez-Peris, M. Patiño-Martinez, P. Valduriez: StreamCloud: A Large Scale Data Streaming System, ICDCS, 2010.

2. V. Zaharia, T. Das, H. Li, T. Hunter, S. Shenker, I. Stoica: Discretized Streams: Fault-Tolerant Streaming Computation at Scale, SOSP, 2013.

3. Peter Pietzuch, Jonathan Ledlie, Jeffrey Shneidman, Mema Roussopoulos, Matt Welsh, and Margo Seltzer: Network-Aware Operator Placement for Stream-Processing Systems, ICDE, 2006.

4. D. Abadi, Y. Ahmad, M. Balazinska et al. : The Design of the Borealis Stream Processing Engine, CIDR, 2005.
 
5. S. Babu, J. Widom: Continuous Queries over Data Streams, SIGMOD Record 30(3), 2001.  

Gustaf Helgesson(slides)

6. B.Gedik, H. Andrade, K. Wu, P. Yu, and M. Doo: SPADE: the system S Declarative Stream Processing Engine , SIGMOD. 2008.  

Haikal Pribadi (slides)
7. E. Zeitler and T.Risch: Massive scale-out of expensive continuous queries, VLDB, 2011.

8. Raymond Cheng,Ji Hong,Aapo Kyrola,Youshan Miao,Xuetian Weng,Ming Wu,Fan Yang,Lidong Zhou,Feng Zhao,Enhong Chen: Kineograph: Taking the Pulse of a Fast-Changing and Connected World, EuroSys, 2012. 

 2014/03/04 Session 7: Data Centric Networking  

  • Start at 10:00 in GS15.
  • Various aspects of networking storategy to deal with high volume data
1.1. T. Koponen, M. Chawla, B. Chun. K. Kim, S. Shenker, A. Ermolinskiy, I. Stoica: A Data-Oriented (and Beyond) Network Architecture, SIGCOMM 2007.

1.2.1. V.  Jacobson, D. Smetters, J. Thornton, M. Plass, N. Briggs, R. Braynard: Networking Named Content, CoNEXT, 2009.

Will Sewell (slides)
1.2.2. VJacobspresentation/S7/Will_DND.pdfon, D. Smetters, J. Thornton, M. Plass, N. Briggs, R. Braynard: Networking Named Content, CACM, January, 2012.

1.3. A. Ghodsi, T. Koponen, B. Raghavan, S. Shenker, A. Singla, and J. Wilcox: Information-Centric Networking: Seeing the Forest for the Trees, HotNets, 2011.
 
1.4. P. Jokela, A. Zahemszky, C. E. Rothenberg, S. Arianfar, and P. Nikander: LIPSIN: Line Speed Publish/Subscribe Inter-networking, SIGCOMM, 2009.

1.5. George Xylomenos, Xenofon Vasilakos, Christos Tsilopoulos, Vasilios A. Siris, and George C. Polyzos: Caching and Mobility Support in a Publish-Subscribe Internet Architecture, IEEE Communication, Vol 50, Issue 7, 2012.

1.6. Md. F. Bari, S. Chowdhury, R. Ahmed, R. Boutaba, and B. Mathieu: A Survey of Naming and Routing in Information-Centric Networks, IEEE Communication, Vol 50, Issue 7, 2012.


  • Content distribution overlay

2. A. Carzaniga, A.L. Wolf: Forwarding in a content-based network, SIGCOMM, 2003.

2.2.1. S. Ratnasamy, P. Francis, M. Handley, R. Karp, S. Shenker: A scalable content addressable network, SIGCOMM, 2001.

Haikal Pribadi (slides)
2.2.2. S. Ratnasamy, M. Handley, R. Karp, S. Shenker:
Application-level multicast using content addressable networks, NGC, 2001.
 
2.3.1. M.J. Freedman, E. Freudenthal, D. Mazières: Democratizing Content Publication with Coral, NSDI, 2004.
2.3.2. M.J. Freedman: Experiences with CoralCDN: A Five-Year Operational View, NSDI, 2010.

  •  Delay Tolerant Networks (DTN) (Network holds data)

lias Giechaskiel (slides)
3.1.1. N. Laoutaris, G. Smaragdakis, P. Rodriguez, R. Sundaram: Delay Tolerant Bulk Data Transfers on the Internet, SIGMETRICS, 2009.
3.1.2. N. Laoutaris, M. Sirivianos, X. Yang, P. Rodriguez: Inter-Datacenter Bulk Transfers with NetStitcher,"  SIGCOMM, 2011.

Niko Stahl (slides)
3.2. M. Grossglauser, D. Tse: Mobility increases the capacity of ad-hoc wireless networks, IEEE/ACM Trans. on Networking, 10:477–486, 2002.
 
3.3. K. Fall: A delay-tolerant network architecture for challenged internets, SIGCOMM, 2003.

 2014/03/11 Session 8: Presentation of Open Source Project Study

  • Start @10:00 in GS15.
  • Presentation of Open Source Project Study by all (20 minutes of presentation including Q&A for each presentation)
  1. 10:00 lias Giechaskiel (GraphChi) Solving Massive Graph Problems in GraphChi (slides)
  2. 10:20 Gustaf Helgesson (Storm) Using Storm to calculate trends for different language editions of Wikipedia (slides)
  3. 10:40 Haikal Pribadi (Spark) Machine Learning in the Cloud with Spark (slides)
  4. 11:00 Will Sewell  (GraphChi) Evaluating Graph Analysis Algorithms on Streaming Graphs Using Graphchi (slides)
  5. 11:20 Niko Stahl (Gaphlab/GraphX) Mining a Large Dynamic Graph: A comparative study of GraphLab and GraphX (slides)

11:45-12:00 Wrap-up Discussion (slides)                                                                                                                                               

Coursework 1 (Reading Club)

The reading club will require you to read between 1 and 3 papers every week. You need to fill out a review_log (MS word format, text format) prior to each session and email me by 12:00 noon on Monday. The minimum requirement of review_log is one per session, but you can read as many as you want and fill the review_log for each paper you read.

At each session, around 3 papers are selected under the session topic, and if you are assigned to present your review work, please prepare 20-25 minutes slides for presenting your review work. Your presented material should also be emailed by the following day Wednesday. You would present your review work approximately twice during the course. The paper includes following two types and you can focus on the specified aspects upon reviewing the paper.

  1. Full length papers 
    • What is the significant contribution?
    • What is the difference from the existing works?
  2. Short length papers 
    • What is the novel idea?
    • What is required to complete the work?

 Coursework 2 (Reports)

The following three reports are required, which could be extended from the reading assignment of the reading club or a different one within the scope of data centric networking.

  1. Review report on a full length of paper (1800 words)
    • Describe the contribution of paper in depth with criticism
    • Crystallise the significant novelty in contrast to the other related work
    • Suggestion for future work
  2. Survey report on sub-topic in data centric networking (aim at 1500-2000 words - max 2000 words)
    • Pick up to 5 papers as core papers in your survey scope
    • Read the above and expand your reading through related work
    • Comprehend your view and finish as your survey paper
    • See how to write a survey paper
  3. Project study and exploration of a prototype (2500 words)
    • What is the significance of the project in the research domain?
    • Compare with the similar and succeeding projects
    • Demonstrate the project by exploring its prototype
    • Please email your project selection (MS word format, text format <150 words) by February 10, 2014
    • Project presentation on March 11, 2014

The reports 1 and 2 should be handed in by the end of 5th week (Feb 21, 2014 - 12:00 noon ) and 7th week (March 14, 2014 - 12:00 noon) of the course (not in any particular order). The report 3 should be by the end of the Lent term (April 4,  2014 - 12:00 noon).

 Assessment

The final grade for the course will be provided as a letter grade or percentage and the assessment will consist of two parts:

  1. 25%: for a reading club (Presentation, participation and review_log)
  2. 75%: for the three reports
    • 20%: Intensive review report
    • 25%: Survey report
    • 30%: Project study

Open Source Projects

See the candidates of Open Source Projects in data centric networking. The list is not exhausted. If you take anything other than the one in the list, please discuss with me. The purpose of this assignment is to understand the prototype of the proposed architecture, algorithms, and systems through running an actual prototype and present/explain to the other people how the prototype runs, any additional work you have done including your own applications and setup process of the prototype. This experience will give you better understanding of the project. These Open Source Projects come with a set of published papers and you should be able to examine your interests in the paper through running the prototype. Some projects are rather large and may require extensive environment and time; make sure you are able to complete this assignment.

How to Read/Review a Paper

The following papers aid how to read/review a paper.

Further supplement: see ‘how to read/review a paper’ section in Advanced Topics in Computer Systems by Steven Hand.

Presentations

Presentations should be about 20-25 minutes long, where you need to cover the following aspects.

  1. What are the background and the problem domain of the paper? What is the motivation of the presented work? What is the difference from the existing works?  What is the novel idea? How did the paper change/unchange the research in the research community?

  2. What is the significant contribution? How did the authors tackle the problem? Did the authors obtain expected result from their trial?

  3. How do you like the paper and why? What is the takeaway message to you (and to research community)? What is required to complete the work?

The following document aids in presenting a review.

How to write a survey paper

A survey paper provides the readers with an exposition of existing work that is comprehensive and organized. It must expose relevant details associated in the surveying area, but it is important to keep a consistent level of details and to avoid simply listing the different works. Thus a good survey paper should demonstrate a summary of recent research results in a novel way that integrates and adds understanding to work in the field. For example, you can take an approach by classifying the existing literature in your own way; develop a perspective on the area, and evaluate trends. Thus, after defining the scope of your survey, 1) classify and organize the trend, 2) critical evaluation of approaches (pros/cons), and 3) add your analysis or explanation (e.g. table, figure). Also adding reference and pointer to further in-depth information is important (summary from Rich Wolski’s note).

 Papers for OS Principles (Distributed Storage and Deterministic Parallelism)

  • Following papers will help you to understand distributed storage and parallelism.
  • Systems Research and System Design
1.  B. Lampson: Hints for Computer Systems Design (Revised), ACM OSR 1983.

  • Distributed Storage
2. S. Ghemawat, H. Gobioff, and S. Leung: The Google File System, ACM SOSP 2003.
3. F. Chang et al: BigTable: A Distributed Storage System for Structured Data, USENIX OSDI 2006.
4. G. DeCandia et al:  Dynamo: Amazon's Highly Available Key-value Store, ACM SOSP 2007.

  • Deterministic Parallelism
5. J. Devietti et al: DMP: Deterministic Shared Memory Multiprocessing, ACM ASPLOS 2009.
6. A. Aviram, et al: Efficient System-Enforced Determistic Parallelism, USENIX OSDI 2010.
7. T. Liu et al: Dthreads: Efficient and Determistic Multithreading, ACM SOSP 2011.

Contact Email

Please email to eiko.yoneki@cl.cam.ac.uk for your submission of course work or any question.