1 Estimation of Link Interference in Static Multi-hop Wireless Networks Jitendra Padhye, Sharad Agarwal, Venkat Padmanabhan, Lili Qiu, Ananth Rao, Brian.

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Estimation of Link Interference in Static Multi-hop Wireless Networks

Jitendra Padhye, Sharad Agarwal, Venkat Padmanabhan, Lili Qiu, Ananth Rao, Brian Zill

Microsoft ResearchUniversity of Texas Austin

University of California, Berkeley

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Infrastructure Wireless Network

Access Point

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Ad-hoc, multi-hop wireless networks

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Motivation

• Interference limits performance of (static) multi-hop wireless networks– Simultaneous transmissions on “nearby” links interact adversely

• Knowledge of which links interfere with each other is useful for: – Capacity estimation [GK00, JPPQ03, …]– Routing [De Couto et. al. 03, DPZ04, …]– Channel assignment [RC05, …] – …

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Hard Problem …• Accurate, physical-level radio modeling is difficult

– Environmental factors, hardware-specific details, …

• Simple experimental measurements are not feasible: – Network with n nodes O(n2) links– Pairwise interference O(n4) experiments– Our testbed:

• 22 nodes, over 100 “good” links over 10,000 link pairs

• May have to repeat experiments periodically!

• Our goal: Efficient experimental methodology to estimate pair-wise interference among all links.

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Previous Work

• Punt on the problem …– Assume that interference information is “known” [JPPQ03, …]

• Use simple heuristics– All links on a path interfere [De Couto et. al. 03, DPZ04, …]

• Pessimistic

– Only links that share endpoint interfere [KN03, …]• Optimistic

– Interference range is twice the communication range [GK00, …]• Not valid in all environments

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Problem Formulation

• Two links, A->B and C->D– Throughputs X and Y when operating individually

– Throughputs XX// // and YY//// when operating simultaneously

• Link Interference Ratio (LIR) = (XX// // +YY// // ) / (X + Y)– LIR = 1 implies no interference– LIR < 1 implies interference– Not just binary: full range of values between 0 and 1.

• Goal: Estimate LIR for all link pairs without requiring O(n4) experiments

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Impact of Interference on Unicast Transmissions: #1

• Carrier sensing– A and C can hear each other. – Only one transmits at a time.

A B

C D

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Impact of Interference on Unicast Transmissions: #2

• Collision of data packets– Transmissions from A and C collide at B– Reception of data fails at B

A B

C D

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Impact of Interference on Unicast Transmissions: #3

• Collision of data and ACK packets– ACK from D collides with data from A– Reception of data fails at B

A B

CD

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Impact of Interference on Unicast Transmissions: Other Possibilities

4. Data/ACK collision prevent reception of ACK at sender

5. ACK/ACK collision

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Key Idea

• Only consider carrier sensing (#1) and data packet collisions (#2)– Ignore ACKs

Broadcast packets are sufficient for measurements

Consider only sender pairs, instead of link pairs

O(n2) experiments instead of O(n4)

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Methodology

Measure A’s receive rate @ B = M

Measure C’s receive rate @ D = N

Measure A’s receive rate @ B = M//

Measure C’s receive rate @ D = N//

Broadcast Interference Ratio (BIR) = (M// + N//) / (M + N)

A

C

D

B

= 1 no interference< 1 interference

Pairwise InterferenceIndividual Broadcasts

Hypothesis: BIR is a good approximation of LIR

BIR for all pairs can be calculated with O(n2) experiments

BIR Captures1. Carrier sensing2. Data/Data collisions

BIR Ignores1. Data/ACK collisions2. ACK/ACK collsions3. AutoRate

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Sample Experimental Result

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0.2

0.4

0.6

0.8

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0 0.1 0.2 0.3 0.4 0.5

Error: Abs(LIR-BIR)

Fra

cti

on

802.11a, full power, 6Mbps, no RTS/CTS. 75 link pairs selected at random.

Average of 5 runs

Median error is zero!

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Summary of results

• BIR is a good approximation for LIR in various scenarios – Low power– 802.11 a/b/g– Autorate

• BIR experiments need to be repeated regularly as link interference patterns change over time.

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Future work

• More evaluation: – outdoor, differential power.

• Interference among larger groups of links (not just pairs)

• Predict interference by passively observing existing traffic?

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Microsoft Research Wireless Mesh Networking Project

http://research.microsoft.com/mesh/

Support for academic researchers– Software (Mesh Academic Resource Toolkit)

» Yes, includes source!– Hardware– $$$

Contact: Victor Bahl ([email protected])

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Backup Slides

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Our Contribution

• An experimental methodology to estimate pair-wise link interference using O(n^2) experiments

• Evaluation of this methodology in a variety of settings using an indoor, 22-node testbed.

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What causes interference between two unicast transmissions?

1. Carrier sensing• Senders can “hear” each other’s transmission

Only one sender sends at a time

2. Collisions• Simultaneous data packet transmissions

One or both data packets lost

• Simultaneous data and ACK transmissions Data and/or ACK packet lost