stealing from an ongoing flow: protocols and prototypes

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

Ashu Sabharwal Rice University

7 Blind Mice

Spear

FanPillar

Cliff

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

• 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

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

• 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)

Ashu Sabharwal 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)

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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

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

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

Ashu Sabharwal Rice University

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

Ashu Sabharwal Rice University

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

Ashu Sabharwal Rice University

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

Ashu Sabharwal Rice University

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 ?

Ashu Sabharwal Rice University

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

Ashu Sabharwal Rice University

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