Stealing From an Ongoing Flow:
Protocols and Prototypes
Ashu Sabharwal
Rice University
EPFL (2007-08)
Joint work with Scott Novich & Debashish
Dash
Microsoft Summit 2008
• Thanks to all the participants & Microsoft
• Big thanks to Ranveer for putting all this together
Ashu Sabharwal
Rice University
7 Blind Mice
QuickTime™ and a
decompressor
are needed to see this picture.
Ashu Sabharwal
Rice University
7 Blind Mice
Ashu Sabharwal
Rice University
7 Blind Mice
Spear
Cliff
Fan
Pillar
Rope
Ashu Sabharwal
Rice University
7 Blind Mice
Cognitive Wireless
Ashu Sabharwal
Rice University
Cognitive Wireless
• Hype or Next Big Thing ?
– Feasibility ?
– Extent of Utility ?
– Impact as big as we will like to believe ?
• Scientific questions
– Relevant problem formulations
– Platforms as technical demonstrators
Ashu Sabharwal
Rice University
Outline
• Testbeds/Platforms [7 minutes]
– TFA
– WARP
• Thought Experiment to a Demo [10 minutes]
– Stealing from an ongoing flow
– Formulation
– Result & protocol
Ashu Sabharwal
Rice University
At-scale: TFA-Rice Mesh Network
QuickTime™ and a
TIFF (Uncompressed) decompressor
are needed to see this picture.
QuickTime™ and a
TIFF (Uncompressed) decompressor
are needed to see this picture.
• In low-income neighbourhood of Houston, Texas
• TFA Charter: To empower with technology
• Deployed: 4000+ real users over 4 Km2
Ashu Sabharwal
Rice University
At-scale: TFA-Rice Mesh Network
QuickTime™ and a
TIFF (Uncompressed) decompressor
are needed to see this picture.
QuickTime™ and a
TIFF (Uncompressed) decompressor
are needed to see this picture.
WARP
• Current TFA speeds peak at 0.5 Mbps/user
• Goal: 4-10X gains
• At-speed: Use WARP for a clean-slate network
Ashu Sabharwal
Rice University
Wireless open-Access Research Platform
• WARP
– Programmable FPGA platform (Virtex IIPro, Virtex 4)
– High-end MIMO (upto 4x4, 60-100 Mbps)
– Frameworks for clean-slate designs
Ashu Sabharwal
Rice University
Wireless open-Access Research Platform
• Multiple Design Flows
– WARP + Matlab = WARPLab (offline design)
– Simulink + Sysgen = WARP_Phy + WARP_MAC (real-time)
– Control & Management Plane = WARPnet (deployed
networks)
Ashu Sabharwal
Rice University
WARP Users
Ashu Sabharwal
Rice University
WARP Users (by end of Summer’08)
Industry (11)
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Xilinx (3 sites)
Nokia Beijing
DRS Signal Solutions
Spectrum Signal Processing
Irvine Sensors
ASTRI (Hong Kong)
Communications Research
Centre
Motorola Bangalore
Microsoft Research Beijing
Toyota Info. Tech
Ericsson Research
Ashu Sabharwal
Academia (15)
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UCSD
UC Irvine
USC
Polytechnic
Rutgers
University of Waterloo
University of Oulu
Nile University
RWTH Aachen University
University of Klagenfurt
UC Riverside
UOIT
UC Santa Cruz
Drexel University
UIUC
Rice University
Applications
• Urban-scale mesh network deployments (TFA-Rice)
– Camp & Knightly, Infocom’08
• MIMO : Sphere detection/decoding
– 3G-LTE, WiMax, 802.11n (Cavallaro’s group)
• PM protocols for low-power handsets
– Liu and Zhong, Mobisys’08
• Cooperative communications
– Random Access Cooperative Systems (Tech Report, Asilomar’08)
• Cognitive wireless (today)
Ashu Sabharwal
Rice University
Purpose of a Testbed
• Verify a concept
– Sanity check & feel good
– Engineering approximation error
• Uncover surprises
– Overhead multiplier effect observed in TFA
– 50X reduction in capacity due to routing packets
– Need at-scale and at-speed systems for such discoveries
• Thought Experiment
– Mantra is “I will build”
– Forces you to start with the correct setup
Ashu Sabharwal
Rice University
Outline
• Testbeds/Platforms [7 minutes]
– TFA
– WARP
• Thought Experiment to a Demo [10 minutes]
– Stealing from an ongoing flow
– Formulation
– Result & protocol
Ashu Sabharwal
Rice University
Two-Flow Network
Primary
Rp
Rs
Secondary
Objective: maximize rate Rs
Constraint: cannot reduce primary’s rate
Ashu Sabharwal
Rice University
Rate Region
Primary
Rp
Cp
Rp
Rs
Secondary
Rs
Cs
• Since interfering links, tradeoff between their rates
• True for any choice of protocols
Ashu Sabharwal
Rice University
Rate Region
hpp
Rp
hps
Cp
Rp
hsp
Rs
hss
Rs
Cs
• The whole region depends on topology
– Topology = {hpp , hss , hps , hsp , … }
• If region is known, then rate Rs is easy to find.
Ashu Sabharwal
Rice University
Key Issue: Lack of Knowledge
Primary
Rp
Cp
Rp
Rs
Secondary
Rs ?
Cs
• Compound Network: The secondary does not know
– the topology
– Rp
• How can it select the Rs ?
Ashu Sabharwal
Rice University
Without Help, Secondary Cannot Send
Rp
Rs
• Without any knowledge, max Rs = 0
• Solution = Cognition
– Snoop to learn
– What can one learn about this region ?
Ashu Sabharwal
Rice University
Information Content in Snooping
Primary
Rp
Rs
Secondary Silent
• Hear and decode all transmissions
– Estimate primary rate, Rp
– eg. by listening to ACKs
• Estimates are never perfect
– Overhearing over noisy wireless channels
Ashu Sabharwal
Rice University
Information Content in Snooping
Primary
Rp
Rp
Rs
Secondary Silent
Rs ?
• Not sufficient information to estimate the region
• Reason: Passive estimation
– No feedback with primary
• Solution: Estimation by perturbation
Ashu Sabharwal
Rice University
Estimation by Perturbation
Rp
Rs
+
Rs
Snoop
• Key requirement: Primary should be adapting its rate to network
conditions (e.g. TCP)
• Feedback increases compound network capacity
Ashu Sabharwal
Rice University
Estimation by Perturbation
Primary reacts
here
Rp
Rs
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Inject packets at a small rate
See if the primary is affected
If not, increase rate till it does
Then adjust
Ashu Sabharwal
Rice University
Secondary rate
Protocol Trajectory
R*s
Ttransmit
time
Tsense
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Slow start
Adapt its rate to find optimal rate
Tunable parameters, Ttransmit, Tsense, Rs
Work in progress: characterize convergence rate
Ashu Sabharwal
Rice University
Secondary rate
Demo on WARP
Rp
R*s
Rs
time
• Primary flow alternating between high and low data
rates
• Secondary (estimation by perturbation)
Ashu Sabharwal
Rice University
Secondary rate
Demo on WARP
Rp
R*s
Rs
time
• Primary flow alternating between high and low data
rates
• Secondary (estimation by perturbation)
• Loss = [R*s(t)-Rs(t)]dt
Ashu Sabharwal
Rice University
Lesson I: Starting Point
• Model as if you will build it
– No network information is available
– Everything has to be estimated
• Directly implementable without any rework
– Prototype demo using WARP
– Work by Scott Novich
Ashu Sabharwal
Rice University
Lesson II: Lack of Information
• Hard to steal from dumb devices (e.g. walkie
talkies)
– They do not react to increased interference
• Easier to steal from “smart systems”
– Allows one to observe their behavior by perturbing
them
Ashu Sabharwal
Rice University
Recap
• Prototyping useful at many levels
– Discovering surprises (TFA Network)
– Thought experiment (this talk)
– Sanity check (demo later)
• Distributed cognitive wireless
– Stealing from dumb devices not possible
– Intelligently stealing from smart devices possible
Ashu Sabharwal
Rice University
Questions ?
WARP: http://warp.rice.edu
TFA: http://tfa.rice.edu
CMC: http://cmc.rice.edu
Ashu Sabharwal
Rice University