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Networks and Distributed Systems a.k.a. G22.3033-010

Networks and Distributed Systems a.k.a. G22.3033-010. Lakshmi Subramanian http://cs.nyu.edu/~lakshmi Jinyang Li http://cs.nyu.edu/~jinyang. Class goals. Help you critically appreciate networks & systems research learn creative problem solving (i.e. doing research) How?

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Networks and Distributed Systems a.k.a. G22.3033-010

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  1. Networks and Distributed Systemsa.k.a. G22.3033-010 Lakshmi Subramanian http://cs.nyu.edu/~lakshmi Jinyang Li http://cs.nyu.edu/~jinyang

  2. Class goals • Help you • critically appreciate networks & systems research • learn creative problem solving (i.e. doing research) • How? • Lectures/readings: discuss state-of-art work • Programming labs: play with real systems • A semester-long research project

  3. Syllabus, grading etc. • http://www.cs.nyu.edu/courses/fall06/G22.3033-010 • Class participation (20%) • Read assigned papers before class! • Two labs (10%) • One project (70%) • Team of 2-3 people (<= 1 Ph.D. student per group) • Start next week • Weekly (or once every two weeks) meetings

  4. Who should take the class? • Grad-level class • Satisfy M.S. requirement of a “project” course • Pre-requisite: • Basic knowledge on networks • Computer Networks (L. Peterson) • An engineering approach to computer networking (S. Keshav) • Programming experience • TCP/IP Illustrated (R. Stevens)

  5. Misc. • Office hours: • Jinyang: 715 Broadway Rm 705, Tue 5-6pm • Lakshmi: Rm 706 Mon 5-6pm • TA: Ja Chen (jchen@cs.nyu.edu)

  6. Next Generation Networks Jinyang Li

  7. Emerging networks • Wireless networks • Sensor networks • Overlays and P2P • Delay tolerant networks (DTNs) • …

  8. Wireless networks

  9. Wireless networks: why now? Proliferation of wifi-enabled devices Faster, cheaper radios and more powerful boxes

  10. Wireless apps: urban mesh Provide cheap, ubiquitous Internet connectivity MIT Cambridge Roofnet http://pdos.lcs.mit.edu/roofnet Google Mountain View pole top network http://wifi.google.com

  11. Wireless apps: connecting rural villages Intel/UC Berkeley/NYU Tier project http://tier.cs.berkeley.edu

  12. Wireless apps: mobile, ad-hoc communication MIT CarTel http://cartel.csail.mit.edu

  13. Wireless networks: challenges • Crappy links • Contention and self-interference • Frequent node/link failures • Many parameters Goal: Robust, high performance designs • MAC layer • Routing layer • Transport layer

  14. Challenge #1: crappy links • Many asymmetric, lossy links

  15. Challenge #2: contention Many nodes access the medium  collisions No way to explicitly detect collisions

  16. Challenge #2: self-interference • A multi-hop flow interferes at successive hops 2 3 4 5 1 • At most every third node can transmit

  17. Challenges #3: dynamism Links/nodes fail and recover frequently Link qualities change over time Time (sec)

  18. Challenge #4: (too) many tunable parameters • Transmission power • Transmission rate • Directional vs. omni antennas • Static vs. dynamic channel assignment • One vs. multiple radios

  19. Current state-of-art MIT Roofnet pair-wise node throughput (11Mbps 802.11b radios)

  20. Sensor networks Beyond host-to-host communication

  21. Sensor networks: why now? Technology is ready Cheaper, smaller, more powerful sensors Sense light, temperature, vibration, humidity, location, pulse, motion, vital sign etc. Monitor environment, collection information Intel Dot UCB Telos Xbow MicaZ

  22. Sensor apps: understanding redwood forests UC Berkeley/Intel Research

  23. Sensor apps: real-time patient tracking Harvard CodeBlue

  24. Sensor-net challenges • Different communication paradigm • host-to-host is the wrong fit • Data-centric • Limited resources • Low radio bandwidth 250Kbps advertised, ~80Kbps in real life • Slow processor, tiny storage 8MHz CPU, 8K RAM • Limited energy

  25. Overlays and P2P Distributed systems meet the Internet

  26. Why p2p/overlay? • A distributed system architecture: • No (minimal) centralized control • Nodes are symmetric in function • Enabled by technology improvements Internet

  27. Large scale wide-area systems Unmanaged (open p2p systems): BitTorrent: >1M nodes Skype: >5M users Managed PlanetLab: 700 nodes over 336 sites Akamai CDN: >10K nodes

  28. What’s new here? • Opportunities: • Huge aggregate capacity Network, storage, processing… • Geographic diversity • Many apps: • File sharing • CDNs • VoIP • Streaming multicast • Usenet news • …

  29. Challenges • How to find data? • How to deal with failures? • Nodes fail and recover • Network outage and partition • (Open networks only) How to deal with selfish or malicious nodes? • provide data integrity • provide privacy or anonymity

  30. Challenge #1: resource discoveryCase study: file sharing • Where is the file named “Hamlet”?

  31. Challenge #2: churn • What if the node with “Hamlet” goes down?

  32. Challenge #3: selfish nodes Selfish nodes do not want to upload “Hamlet” I do NOT have Hamlet

  33. Challenge #4: malicious nodes I HAVE junk named Hamlet • Malicious nodes lie about their contents

  34. Next week Naming and addressing Project ideas

  35. Distributed systems in a data-center • Connected by LANs low loss and delay • Provide infrastructural services for apps • Network file systems • Databases • Distributed data processing Check out the Spring class “distributed storage systems”

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