stealing from an ongoing flow: protocols and prototypes ashu sabharwal rice university epfl...
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Stealing From an Ongoing Flow: Protocols and Prototypes
Ashu SabharwalRice UniversityEPFL (2007-08)
Joint work with Scott Novich & Debashish Dash
Ashu Sabharwal Rice University
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
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Ashu Sabharwal Rice University
7 Blind Mice
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7 Blind Mice
Spear
FanPillar
Cliff
Rope
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7 Blind Mice
Cognitive Wireless
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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
• In low-income neighbourhood of Houston, Texas• TFA Charter: To empower with technology• Deployed: 4000+ real users over 4 Km2
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Ashu Sabharwal Rice University
At-scale: TFA-Rice Mesh Network
• Current TFA speeds peak at 0.5 Mbps/user• Goal: 4-10X gains • At-speed: Use WARP for a clean-slate network
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WARP
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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
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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
• 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
WARP Users (by end of Summer’08)
Industry (11) Academia (15)
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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)
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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
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Outline
• Testbeds/Platforms [7 minutes]– TFA– WARP
• Thought Experiment to a Demo [10 minutes]– Stealing from an ongoing flow– Formulation– Result & protocol
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Two-Flow Network
Objective: maximize rate Rs
Constraint: cannot reduce primary’s rate
Primary
Secondary
Rp
Rs
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Rate Region
• Since interfering links, tradeoff between their rates
• True for any choice of protocols
Primary
Secondary
Rp
Rs
Rp
Rs
Cp
Cs
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Rate Region
• The whole region depends on topology– Topology = {hpp , hss , hps , hsp , … }
• If region is known, then rate Rs is easy to find.
hpp
Rp
Rs
Rp
Rs
Cp
Cs
hss
hps
hsp
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Key Issue: Lack of Knowledge
• Compound Network: The secondary does not know – the topology
– Rp
• How can it select the Rs ?
Primary
Secondary
Rp
Rs
Rp
Rs ?
Cp
Cs
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Without Help, Secondary Cannot Send
• Without any knowledge, max Rs = 0
• Solution = Cognition– Snoop to learn– What can one learn about this region ?
Rp
Rs
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Information Content in Snooping
• Hear and decode all transmissions– Estimate primary rate, Rp
– eg. by listening to ACKs
• Estimates are never perfect– Overhearing over noisy wireless channels
Primary
Secondary Silent
Rp
Rs
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Information Content in Snooping
• Not sufficient information to estimate the region
• Reason: Passive estimation– No feedback with primary
• Solution: Estimation by perturbation
Primary
Secondary Silent
Rp
Rs
Rp
Rs ?
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Estimation by Perturbation
• Key requirement: Primary should be adapting its rate to network conditions (e.g. TCP)
• Feedback increases compound network capacity
Rp
Rs +
Snoop
Rs
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Estimation by Perturbation
• Inject packets at a small rate• See if the primary is affected• If not, increase rate till it does• Then adjust
Rp
Rs
Primary reacts here
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Protocol Trajectory
• Slow start• Adapt its rate to find optimal rate
• Tunable parameters, Ttransmit, Tsense, Rs
• Work in progress: characterize convergence rate
R*s
Secondary rate
timeTtransmit
Tsense
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Demo on WARP
• Primary flow alternating between high and low data rates
• Secondary (estimation by perturbation)
Secondary rate
time
Rp
R*s
Rs
Ashu Sabharwal Rice University
Demo on WARP
• Primary flow alternating between high and low data rates
• Secondary (estimation by perturbation)
• Loss = [R*s(t)-Rs(t)]dt
Secondary rate
time
Rp
R*s
Rs
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
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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
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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.eduTFA: http://tfa.rice.eduCMC: http://cmc.rice.edu