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An Experimental Evaluation of Selective Cooperative Relaying for Industrial Wireless Sensor Networks Nikolaj Marchenko, Torsten Andre, G unter Brandner, Wasif Masood, and Christian Bettstetter Institute of Networked and Embedded Systems


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SLIDE 1

An Experimental Evaluation of Selective Cooperative Relaying for Industrial Wireless Sensor Networks

Nikolaj Marchenko, Torsten Andre, G¨ unter Brandner, Wasif Masood, and Christian Bettstetter

Institute of Networked and Embedded Systems University of Klagenfurt, Austria

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SLIDE 2

Quick Intro

S R D

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SLIDE 3

Quick Intro

S R D

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SLIDE 4

Quick Intro

◮ Lots of theoretical work on cooperative relaying ◮ Some experimental studies (40+ articles): 1 Software-Defined Radios: Mostly PHY Layer, few nodes 2 Wireless Sensor Nodes: MAC/Network layer, many nodes

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SLIDE 5

Application in Industrial WSN

◮ Monitoring and control of production processes ◮ Harsh environment for wireless signal propagation ◮ Very strict requirements on link reliability and delay ◮ Standards: WirelessHART, ISA100.11a, Zigbee IA Profile

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Relay Selection

Relay Selection

1 Which metrics to use for relay selection?

◮ Channel quality info, residual battery life, etc.

2 How selection is coordindated?

◮ Signaling messages, contention mechanism, etc.

3 How often a relay is updated?

◮ Update requirements and policy.

S R D

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SLIDE 7

Relay Selection

  • I. Periodic Relay Selection

A relay is selected strictly at periodic time intervals Tsel

◮ random contention of candidates in window w. ◮ based on current Link Quality Indicators S − R and R − D.

selection retransmission S Ri D S_RREQ (bc) D_RSEL rand(0,w) R_CAND R_RSEL

S Ri D DATA (mc) ACK (mc) TACK DATA ACK

err

DATA (mc) ACK (mc) ACK TACK

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SLIDE 8

Relay Selection

  • II. Adaptive Selection

◮ A new relay selection when in a window Wa more than εa

ACKs are lost.

◮ Selection and retransmission procedure same as periodic

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SLIDE 9

Relay Selection

  • III. Reactive Selection

Selection is performed after each missing ACK for direct S-D transmissions among nodes that

1 have received the packet correctly 2 have a good channel to the destination

DATA delivery by S fails DATA is delivered by S

S Ri D DATA (bc) ACK (mc) TACK DATA ACK

err

S_RREQ (bc)

D_RSEL R_CAND

relay selection

rand(0,w)

S Ri D DATA (bc) TACK ACK

S_RREQ (bc) rand(0,w)

ACK (bc) DATA (bc) TACK ACK (bc)

err no err ACK err

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SLIDE 10

Test Environment

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SLIDE 11

Test Environment

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SLIDE 12

Hardware

◮ Crossbow TelosB ◮ TinyOS implementation ◮ Transmission: 2.4 GHz, 256 kbit/s, TxPower: -4 dBm

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SLIDE 13

Layout

◮ 7 nodes, 6 tested links

D

60m 25m

◮ Two kind of experiments: 1 Trace-based analysis on individual link:

Node 6 transmits to D every 160 ms, other nodes retransmit

2 Explicit experimental comparison over all links

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SLIDE 14

Performance Results: Trace-Based Analysis

1 Periodic selection: every 200 packets 2 Adaptive selection: if error rate > 10% for last 50 packets.

Number of neighboring nodes

node combination id delivery ratio reactive periodic adaptive 3 nodes 4 5 direct transmissions only time diversity 2 nodes 1 node 5 10 15 20 25 30 0.4 0.4 0.5 0.6 0.7 0.8 0.9 1

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SLIDE 15

Performance Results: Trace-Based Analysis

Periodic selection

selection period, data packets delivery ratio 1 2 3 5 100 101 102 0.7 0.75 0.8 0.85 0.9 0.95 selection period in pkts number of selection per 100 data pkts 1 2 3 4 5 # relays 100 101 102 10−1 100 101 102

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Performance Results: Trace-Based Analysis

Adaptive selection: Window

window size, Wa delivery ratio N = 3, 4, 5 N = 2 N = 1 50 100 150 200 250 300 0.7 0.75 0.8 0.85 0.9 window size, Wa selections per 100 data packets 1 2 3 4 5 50 100 150 200 250 300 10−1 100 101 102

Adaptive selection: Error rate

error rate threshold, εa total delivery ratio 1 2 3 5 0.2 0.4 0.6 0.8 1 0.7 0.75 0.8 0.85 0.9 error rate threshold, εa selections per 100 data packets 1 2 3 5 0.2 0.4 0.6 0.8 1 10−3 10−2 10−1 100 101 102

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Direct Comparison

periodic adaptive reactive time 160ms 160ms 160ms time div. time div. 160ms

Sample # Delivery ratio per sample Exp.2. Test:3081 direct periodic adaptive reactive 500 1000 1500 2000 0.8 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 16/21

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Performance Results: Direct Comparison

◮ Measurements on 3 days, each 12 hours. ◮ Total 810K DATA packets sent by source nodes ◮ 33K on each link and each scheme, over 6 hours time. ◮ Periodic selection: Tsel = 400 · 160 ms = 64sec ◮ Adaptive selection: Wa = 100, εa = 0.1

Table: Mean Results over the Network

direct time div. periodic adaptive reactive delivery ratio, % 81.2 85.7 96.9 97.9 98.9 selections per 100 pkts

  • 1.08

1.11 22.7 number of candidates

  • 3.69

3.86 3.43 selection success, %

  • 94

91 92 relaying success,%

  • 78

82 95

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SLIDE 19

Performance Results: Direct Comparison

Delivery ratio in a sample

delivery ratio in a sample cdf single direct transmission time diversity periodic adaptive reactive 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 10−3 10−2 10−1 100

Selections in a sample

time diversity periodic delivery ratio by a single direct transmission in a sample total delivery ratio adaptive reactive 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 18/21

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Performance Results: Direct Comparison

Delivery ratio in a sample

number of retransmission rounds cdf time diversity periodic adaptive reacitve 100 101 102 0.9 0.5 0.55 0.6 0.65 0.7 0.75 0.8 0.85 0.9 0.95 1

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SLIDE 21

Conclusions

1 Cooperative relaying provides up to 99% delivery ratio 2 Short-term outages are also avoided 3 Adaptive selection provides best tradeoff between delivery

ratio and selections overhead Publications

◮ N. Marchenko, et al.

An Experimental Study of Selective Cooperative Relaying in Industrial Wireless Networks. Under review in IEEE Trans. Industrial Informatics, 2013.

◮ T. Andre, et al. WiNMee Workshop, May 2013. ◮ T. Andre, et al. GLOBECOM’12.

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Finally the Final Slide

Thank You for Your Attention!

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