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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

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

Lakshmi Subramanian

http://cs.nyu.edu/~lakshmi

Jinyang Li

http://cs.nyu.edu/~jinyang

class goals
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
syllabus grading etc
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
who should take the class
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)
slide5
Misc.
  • Office hours:
    • Jinyang: 715 Broadway Rm 705, Tue 5-6pm
    • Lakshmi: Rm 706 Mon 5-6pm
    • TA: Ja Chen (jchen@cs.nyu.edu)
emerging networks
Emerging networks
  • Wireless networks
  • Sensor networks
  • Overlays and P2P
  • Delay tolerant networks (DTNs)
wireless networks why now
Wireless networks: why now?

Proliferation of wifi-enabled devices

Faster, cheaper radios and more powerful boxes

wireless apps urban mesh
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

wireless apps connecting rural villages
Wireless apps: connecting rural villages

Intel/UC Berkeley/NYU Tier project

http://tier.cs.berkeley.edu

wireless apps mobile ad hoc communication
Wireless apps: mobile, ad-hoc communication

MIT CarTel

http://cartel.csail.mit.edu

wireless networks challenges
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
challenge 1 crappy links
Challenge #1: crappy links
  • Many asymmetric, lossy links
challenge 2 contention
Challenge #2: contention

Many nodes access the medium  collisions

No way to explicitly detect collisions

challenge 2 self interference
Challenge #2: self-interference
  • A multi-hop flow interferes at successive hops

2

3

4

5

1

  • At most every third node can transmit
challenges 3 dynamism
Challenges #3: dynamism

Links/nodes fail and recover frequently

Link qualities change over time

Time (sec)

challenge 4 too many tunable parameters
Challenge #4: (too) many tunable parameters
  • Transmission power
  • Transmission rate
  • Directional vs. omni antennas
  • Static vs. dynamic channel assignment
  • One vs. multiple radios
current state of art
Current state-of-art

MIT Roofnet pair-wise node throughput (11Mbps 802.11b radios)

sensor networks

Sensor networks

Beyond host-to-host communication

sensor networks why now
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

sensor net challenges
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
overlays and p2p

Overlays and P2P

Distributed systems meet the Internet

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

Internet

large scale wide area systems
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

what s new here
What’s new here?
  • Opportunities:
    • Huge aggregate capacity

Network, storage, processing…

    • Geographic diversity
  • Many apps:
    • File sharing
    • CDNs
    • VoIP
    • Streaming multicast
    • Usenet news
challenges
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
challenge 1 resource discovery case study file sharing
Challenge #1: resource discoveryCase study: file sharing
  • Where is the file named “Hamlet”?
challenge 2 churn
Challenge #2: churn
  • What if the node with “Hamlet” goes down?
challenge 3 selfish nodes
Challenge #3: selfish nodes

Selfish nodes do not want to upload “Hamlet”

I do NOT have

Hamlet

challenge 4 malicious nodes
Challenge #4: malicious nodes

I HAVE junk named Hamlet

  • Malicious nodes lie about their contents
next week
Next week

Naming and addressing

Project ideas

slide36

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”