Department of Computer Science University of Virginia

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Addressing Burstiness for Reliable Communication and Latency Bound Generation in Wireless Sensor Networks. Department of Computer Science University of Virginia. Sirajum Munir , Shan Lin, Enamul Hoque, S. M. Shahriar Nirjon, John A. Stankovic, and Kamin Whitehouse. Problem Definition. - PowerPoint PPT Presentation

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Addressing Burstiness for Reliable Communication and Latency Bound

Generation in Wireless Sensor Networks

Department of Computer ScienceUniversity of Virginia

Sirajum Munir, Shan Lin, Enamul Hoque, S. M. Shahriar Nirjon, John A. Stankovic, and Kamin Whitehouse

Problem Definition

• Reliable delivery– Retry on each link until the

packet is receivedN1 N2 N3

N4 N5N6 N7

N8 N9N10

Source

Destination

23 3

5

Problem Definition

• Reliable delivery– Retry on each link until the

packet is received

• Problem:– Unbounded E2E latency– Not acceptable for real-time

applications

N1 N2 N3

N4 N5N6 N7

N8 N9N10

Source

Destination

Overview

• Basic Approach– Estimate maximum “burst”

length for each link• #consecutive failures

N1 N2 N3

N4 N5N6 N7

N8 N9N10

Source

23

3 200

335

3

5

100

5

4 562

2

Destination

Overview

• Basic Approach– Estimate maximum “burst”

length for each link

– Key insight:• Burstiness caused by physical

world dynamics• Some links are relatively

insulated from these dynamics

N1 N2 N3

N4 N5N6 N7

N8 N9N10

Source

23

3 200

335

3

5

100

5

4 562

2

Destination

Overview

• Basic Approach– Estimate maximum “burst”

length for each link– Choose routes that only use

non-bursty links

N1 N2 N3

N4 N5N6 N7

N8 N9N10

Source

23

3 200

335

3

5

100

5

4 562

2

Destination

Overview

• Basic Approach– Estimate maximum “burst”

length for each link– Choose routes that only use

non-bursty links– Schedule packet transmission

to avoid interference between links

N1 N2 N3

N4 N5N6 N7

N8 N9N10

Source1 Destination2

Source2 Destination1

Outline

• Modeling link burstiness• E2E latency bounds• Evaluation

Modeling Burstiness

• Modeling link Bursts– Bmax, B’min per link

• Bmax = Maximum No. of time slots where transmission can fail

• B’min = Minimum No. of time slots available for transmission

• W = Bmax + B’min

– Example• B’min = 1• W = 2

1 0 0 1 1 0 1 …

Modeling Burstiness

• Modeling link bursts– Bmax, B’min per link

• Bmax = Maximum No. of time slots where transmission can fail

• B’min = Minimum No. of time slots available for transmission

• W = Bmax + B’min

– Example• B’min = 1• W = 3• Bmax = 2

1 0 0 1 1 0 1 …

Modeling Burstiness

• Different from existing models– The β Factor [Srinivasan et al.]

• Models burstiness based on the distribution of burst lengths

– Our model only cares about the maximum burst length

X X X X X X X X X …

Empirical Study

• 21 Days-long • Indoor testbed• 48 Tmote Sky nodes • 3.6 M packets/link• 200 packets/sec• Compute Bmax, B’min, PRR of every link

Empirical Study

• Verified:– Some links are very bursty– Some links are not bursty

• Bmax is not predicted by PRR– Some highly reliable links

(PRR>0.99) still have very large bursts

Outline

• Modeling link burstiness• E2E latency bounds• Evaluation

E2E Latency Bound

• Min Latency Bound: NP-Hard• Greedy solution: Principles

– Routing : Least burst routing

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N4 N5N6 N7

N8 N9N10

Source

Destination

N1 N2 N3

N4 N5N6 N7

N8 N9N10

Source

Destination

Bmax

BmaxBmax Bmax

Bmax

Bmax

Bmax

Bmax

Bmax

Bmax

Bmax

BmaxBmax

Bmax

E2E Latency Bound

• Greedy solution : Principles– Routing: Least burst route– Schedule packet transmission

• Allocating time slots:– How many time slots to allocate per link?

» Allocate Bmaxi+1 contiguous time slots, for i-th link

– Can we do even better?» Yes ! Overlap some streams’ time slot allocation

N1 N2 N3

N4 N5N6 N7

N8 N9N10

Source

Destination

E2E Latency Bound

• What is overlapping?– Assume Link L(1,2) has Bmax=2, B’min=4

– 2 Streams: S1, S2

• Why do we need overlapping ?– W/O overlapping: Avg LB = (3 + 6)/2 = 4.5– W/ overlapping: Avg LB = (3 + 4) /2 = 3.5

N1 N2

1 2 3 4 5 6

S1 S1 S1

S2 S2 S2

Schedule w/o overlapping

1 2 3 4

S1 S1 S1

S2 S2 S2

Schedule w/ overlapping

Prioritizing rule

Time Slots

E2E Latency Bound

• How much to overlap?– Assume Link L(1,2) has Bmax=2, B’min=4

– 2 Streams: S1, S2

– Overlap at most B’min number of streams

N1 N2

1 2 3

S1 S1 S1

S2 S2 S2

Complete overlapping: Doesn’t work !

1 2 3 4 5 6

S1 S1 S1

S2 S2 S2

S3 S3 S3

S4 S4 S4

Time Slots

Time Slots

E2E Latency Bound

• How much to overlap?– Assume Link L(1,2) has Bmax=2, B’min=4

– 2 Streams: S1, S2

– Overlap at most B’min number of streams

N1 N2

1 2 3

S1 S1 S1

S2 S2 S2

Complete overlapping: Doesn’t work !

1 2 3 4 5 6

S1 S1 S1

S2 S2 S2

S3 S3 S3

S4 S4 S4

Time Slots

Time Slots

E2E Latency Bound

• How much to overlap?– Assume Link L(1,2) has Bmax=2, B’min=4

– 2 Streams: S1, S2

– Overlap at most B’min number of streams

N1 N2

1 2 3

S1 S1 S1

S2 S2 S2

Complete overlapping: Doesn’t work !

1 2 3 4 5 6

S1 S1 S1

S2 S2 S2

S3 S3 S3

S4 S4 S4

Time Slots

Time Slots

E2E Latency Bound Summary

• Greedy solution : Principles– Routing: Least burst routing– Allocating time slots:

• How many time slots to allocate per link?– Bmaxi+1 contiguous time slots

– Without complete overlapping

• How much to overlap?– Overlap at most B’mini streams’ time slot allocation

• How to handle interference?– Use IM to avoid interference

Outline

• Modeling link burstiness• E2E latency bounds• Evaluation

Evaluation

• Experimental Setup– Same testbed as empirical study

• 48 Tmote Sky nodes

– Same packet transmission rate• 200 packets/sec

– RBS style time-synchronization

• Effect of Bmax– B’min = 1– Multiplying factor: K

• Allocate Bmaxi*K + 1 time slots, for i-th link

– As K increases• Average LB increase linearly • E2E DMR becomes 0

at K = 0.6 !• Allocate Bmaxi*0.6 + 1

time slots -> save 12.4% latency

– K allows us to control E2E DMR and LB !

• Avg. LB increases linearly

Evaluation

12.4%

Evaluation

• Effect of B’min– As B’min increases

• LB decreases• Then starts to increases again !

– Minimize average LB by an intelligent selection of B’min.

Contributions

• New model of link burstiness– Estimates maximum consecutive packet loss – Not captured by β factor or PRR

• New scheduling algorithms for E2E latency bounds

• Empirical evaluation– 21 day link characterization– Testbed evaluation of LB miss ratio with 10

simultaneous streams

Conclusions

• Can provide reasonable estimate of latency bounds– Not a guarantee– The “K” parameter helps control the trade-off between

miss ratio and latency

• One important step to combine wireless networking with real-time control

Questions?

Backup Slides

One Final Issue…

• Change in burst behavior?– Packet Recovery

• Each node queues un-transmitted packets.• Transmits later if free slot available.

– Link Adaptation• Each node keeps a record when it fails to transmit• Sends this report to B.S. periodically• B.S. reschedules by doubling/ halving the allocated

time slots• LB expands/shrinks dynamically

Stationarity

• Can we assume that Bmax is stationary?– Can classify links:

• Bursty links had highly variable Bmax• Non-bursty links were more consistent

– Why? Due to physical dynamics

– Must ensure that measurement period captures all physical dynamics

• No stronger requirement than any model

IM

• Characterizing Interference:– Define an Interference Matrix, IM

– Measurement based on PRR

otherwise 0,

range ceinterferen in are Lj link and Li linkif 1,j)IM(i,

Ni1 Ni2

Nj1 Nj2

Li

Lj

L1 L3

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