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Embedded Networks Laboratory

Interference-Aware Fair Rate Control in Wireless Sensor Networks (IFRC)

Sumit Rangwala

Ramakrishna Gummadi, Ramesh Govindan, Konstantinos Psounis

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Embedded Networks Laboratory

Problem Definition• Wireless network of N

nodes– Data transmission over

multiple hops to a single node

“Design a distributed algorithm to dynamically allocate fair and efficient rate to each flow”

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Embedded Networks LaboratoryMotivation: A Wireless Sensor

Network for Collecting Structural Vibrations

• Nodes measured vibrations and transmitted it to a central node– Over multiple hops

• Preconfigured rates for each flow– Led to congestion

• More than an hour to receive 10 min of vibration data in a 15 node network

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Embedded Networks Laboratory

Assumptions• CSMA MAC (without

RTS/CTS)• Link-layer

retransmissions• Routing Tree • One flow originating per

node

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Assumptions consistent with current practice in sensornets

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Embedded Networks Laboratory

Challenges• Goal

– Max-min allocation• Wireless Networks

– Transmission rate from a node to its neighbor depends on neighborhood traffic

– Flows affecting this transmission rate are not merely flows traversing a node.

fi

fj

A

B

m

n

Flows that affect each others' rate may not traverse a common link or node

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Embedded Networks Laboratory

Challenges• Transmission rate along 16

→14– Dependent on traffic on

various other links• 20 → 16, 21 → 16, 14 → 12 • 17 →14, 13 →11, 12 →10

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• The rate of flows traversing 16 →14 (flows from 20, 21, and 16)– … is affected by rate of:

• Flows originating from 17, 14, 13, 12,

• As well as 15, 18, 19

• Transmission rate along 16 →14– Dependent on traffic on

various other links• 20 → 16 (a) , 21 → 16 (b), 14

→ 12 (c) • 17 →14, 13 →11, 12 →10

• Transmission rate along 16 →14– Dependent on traffic on

various other links• 20 → 16 (a) , 21 → 16 (b), 14

→ 12 (c) • 17 →14 (d), 13 →11 (e), 12

→10 (f)

• Transmission rate along 16 →14– Dependent on traffic on

various other links• 20 → 16 (a) , 21 → 16 (b), 14

→ 12 (c) • 17 →14 (d), 13 →11 (e), 12

→10 (f)

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Embedded Networks Laboratory

Definition: Potential Interferer

Interfering links l1 interferes with a link l2 if transmission along l1 prevents

– initiation of a transmission along l2 or – successful reception of a transmission

along l2.

Potential interferer Node n1 is a potential interferer of node n2 if

– flow originating from node n1 uses a link that interferes with the link n2 → parent(n2).

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For CSMA and many-to-one trafficpotential interferer (ni) includes

– neighbors of ni

– neighbors of parent(ni)– Descendents of all the above nodes

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Embedded Networks Laboratory

IFRC Design• Congestion Detection

– Based on avg. queue length

• Congestion Sharing– To all the potential

interferers

• Rate Adaptation– AIMD

rlocal (rate of flow from this node)Forwarding Traffic

Packet transmitted until queue is empty (with retransmission)

Queue at each node

IFRC adapts rate of flow originating at a node, not the rate of flows traversing the node

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Embedded Networks Laboratory

Congestion Detection and Rate Adaptation

• Congestion Detection– Based on queue length calculated as

qavg = wq * qinst + (1- wq) * qavg

– Thresholding

• Rate Adaptation – Every 1/rate sec (Additive Increase)

rate = rate + δ / rate

– On local congestion (Multiplicative Decrease) rate = rate/2

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Embedded Networks Laboratory

Congestion Sharing• Each node piggybacks on every transmitted

packet– Its own rate (rlocal) and its congestion state– Rate and congestion state of its most congested child

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Embedded Networks Laboratory

Congestion SharingRule 1:

Local rate of a node should not be greater than that of its parent

(rlocal < rparent)

Rule 2: For any congested neighbor or congested child of a neighbor

Local rate should not be greater than the rate of

the congested node (rlocal < rcongested node)

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These rules are sufficient to signal all potential interferers

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Embedded Networks Laboratory

Parameter Selection• Additive Increase

– δ = rate of increase• Analytically characterize δ to ensure stability

,8 0UF

K jjFs

UK 21

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Queue Threshold

Queue Threshold

Avg. depth of the tree

Network size and topology

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Embedded Networks Laboratory

Evaluation on Sensor Testbed

• Platform– Tmote Sky – TinyOS 1.1.15

• Setup– 40 node testbed

• Network diameter = 8 hops

– Static routing tree• Depth of the Tree = 9

hops• Link quality varied from

66% to 96%• Each experiment was

conducted for an hour

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4th Floor

Base Station

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Embedded Networks Laboratory

TopologyBase Station

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Embedded Networks Laboratory

Per Flow Goodput and Packet Reception

Average goodput as well as the instantaneous goodput is fair

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Embedded Networks Laboratory

Comparison with Optimal

IFRC achieves 60-80% of the optimal fair rate

IFRC achieves 80% of the optimal fair rate

IFRC achieves 60% of the optimal fair rate

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Embedded Networks Laboratory

Rate Adaptation and Instantaneous Queue Length

Not a single drop due to queue overflow

Max Buffer Size = 64

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Embedded Networks Laboratory

Weighted Fairness• IFRC works without modification

– Sending rate = weight* rlocal pkts/sec

w = 1 w = 1w = 2

IFRC assigns rate proportional to node weight

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Embedded Networks Laboratory

Multiple Sink• Two base stations rooted

at 1 and 41– Nodes get rates that are

fair across trees

• IFRC is efficient – Node 4,5 and 6 get greater

(but equal) rates • Their flows don’t traverse

the most congested region.

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Embedded Networks Laboratory

Conclusions• Analysis of set of flows that share congestion at

a node – Potential interferers

• Design and implementation of low-overhead rate control mechanism

• Analysis of IFRC’s steady-state behavior – Provide guidelines for parameters selection

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Embedded Networks Laboratory

Thank You• For more Information

– http://enl.usc.edu/~srangwal/projects/ifrc.html

• Code– Tinyos contrib

• tinyos-1.x/contrib/usc-ifrc– ENL public CVS

• http://enl.usc.edu/cgi-bin/viewcvs/viewcvs.cgi/ifrc

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Embedded Networks Laboratory

Backup Slides

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Embedded Networks Laboratory

Definition: Fair and Efficient Allocation

• fi flow originating from node i• Fi flows routed through node I

1. At each node i, define Ғi to be the union of Fi and all sets Fj

• where j is either a neighbor of i, or a neighbor of i’s parent. These flows are flows from i’s potential interferers.

2. Allocate to each flow in Ғi a fair and efficient share of the nominal bandwidth B. Denote by fl,i the rate allocated at node i to flow l.

3. Repeat this calculation for each node.

4. Assign to fl the minimum of fl,i over all nodes i.

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Embedded Networks Laboratory

Related Work• Sensornets

– Graceful, fair, degradation under load [Hull et al. (Fusion), Wan et al. (CODA)]

– Centralized rate allocation [Sankarasubramaniam et al. (ESRT), Ee et al.]

– AIMD-based rate adaptation without congestion sharing [Woo et al.]

• Wireless ad-hoc networks– Congestion sharing heuristics for any-to-any communication

[Xu et al. (NRED)]

Unlike prior work, we precisely identify the set of potential interferers

These heuristics don’t precisely identify the set of potential interferers

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Embedded Networks Laboratory

Congestion Detection• Based on queue length calculated as EWMA

qavg = wq * qinst + (1- wq) * qavg

• Multiple thresholds– Lower threshold L – Upper thresholds U(k) = U(k-1) + I/2k-1

• U(0) = U

L U U + I U + 3I/2

Local Congestion

Local Congestion

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Embedded Networks Laboratory

Rate Adaptation• Slow start

– Starts with rate = rinit – Every 1/ rate sec

• rate = rate + Φ

• Slow start ends when – node itself get congested– constrained by other nodes to reduce its rate

• Congestion sharing

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Embedded Networks Laboratory

Congestion Detection andRate Adaptation

ri remains unchanged

L U

every 1/ri secri = ri+δ/ri

ri = ri /2

U + I U + 3I/2

ri = ri /2 ri = ri /2

every 1/ri secri = ri+δ/ri

Rate adaptation with changing queue size

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Embedded Networks Laboratory

Base Station• Maintains rbase station, like rlocal of any other node, to share

congestion across nodes• Follows the same algorithm for rate adaptation with one

exception– Decreases rbase station only when a child of base station is

congested.• It does not decreases its rate when any other neighbor is

congested or any child of a neighbor is congested.

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Embedded Networks Laboratory

Parameter Selection (Steady State)

• Additive increase

• Constraint on ε

• U0 and U1 based on [Floyd et al.]• Rule of thumb for Fj

– (n = size of network)

ir min,2

nnFj log

08UFj

jFs

U2

1

2

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,i

ii rrr

)(

)())(

1(tr

trtr

tri

ii

i

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Embedded Networks Laboratory

Evaluation (Tree)

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Embedded Networks Laboratory

Parameters Used

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Embedded Networks Laboratory

Comparison with Optimal

Max Queue Length

IFRC achieves 60-80% of the optimal fair rate

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Embedded Networks Laboratory

Node Addition

Nodes join

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Embedded Networks Laboratory

Node Deletion

Nodes leave

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Embedded Networks LaboratoryIFRC (No Link Layer

Retransmissions)

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Embedded Networks Laboratory

Subset of node • Special case of weighted fairness

– nodes with no data to send ≡ weight = 0

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Embedded Networks Laboratory

Multiple Sink (Trees)

Base Stations