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1 Asset Tracking with Roll-Call TM : Design, Deployment and Analysis Yanyong Zhang, Ben Firner, Rich Howard, Wade Trappe WINLAB, Rutgers University

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Page 1: Design, Deployment and Analysis - WINLAB · 1. Asset Tracking with Roll-Call. TM: Design, Deployment and Analysis. Yanyong Zhang, Ben Firner, Rich Howard, Wade Trappe. WINLAB, Rutgers

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Asset Tracking with Roll-CallTM: Design, Deployment and Analysis

Yanyong Zhang, Ben Firner, Rich Howard, Wade Trappe

WINLAB, Rutgers University

Page 2: Design, Deployment and Analysis - WINLAB · 1. Asset Tracking with Roll-Call. TM: Design, Deployment and Analysis. Yanyong Zhang, Ben Firner, Rich Howard, Wade Trappe. WINLAB, Rutgers

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RFID: Technology of the Future RFID: Technology of the Future We envision that an efficient asset tracking application should:•

Continuously track the position of each item•

Detect the missing of an item in real time•

E.g., jewelry tracking

Page 3: Design, Deployment and Analysis - WINLAB · 1. Asset Tracking with Roll-Call. TM: Design, Deployment and Analysis. Yanyong Zhang, Ben Firner, Rich Howard, Wade Trappe. WINLAB, Rutgers

MooreMoore’’s Law (Techie View)s Law (Techie View)

Year

1010

10 9

10 8

10 7

10 6

10 5

10 41970 1980 1990 2000 2010

Encyclopedia2 hrs CD Audio30 sec HDTV

Book1 min CD Audio1/4 sec HDTV

Page

No.

of B

its/C

hip

0.15μm

0.15-0.2μm

0.25-0.3μm

0.35-0.4μm

1.0-1.2μm

0.5-0.6μm

0. 7-0.8μm

0.6-2.4μm

4Gb

1Gb

256Mb

64Mb

16Mb

4Mb

1Mb

256Kb

64Kb

Page 4: Design, Deployment and Analysis - WINLAB · 1. Asset Tracking with Roll-Call. TM: Design, Deployment and Analysis. Yanyong Zhang, Ben Firner, Rich Howard, Wade Trappe. WINLAB, Rutgers

MooreMoore’’s Law (Business View)s Law (Business View)

Year

No.

of M

Bits

/Chi

p

0500

1,0001,5002,0002,5003,0003,5004,000

1982

1985

1988

1991

1994

1997

2000

2003

Dumb Idea !

Start Study

Out of business

Page 5: Design, Deployment and Analysis - WINLAB · 1. Asset Tracking with Roll-Call. TM: Design, Deployment and Analysis. Yanyong Zhang, Ben Firner, Rich Howard, Wade Trappe. WINLAB, Rutgers

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Limitations with Existing RFIDLimitations with Existing RFIDPassive RFID Tags

+ Inexpensive+ Long Lifetime-

Poor Range

Active RFID Tags+ Good Range- More Expensive-

Short Lifetime

- Larger

Passive Tag Reader

Passive Tag Reader

Anyone there?

Active Tag Receiver

Active Tag Receiver

I’m still here!

Page 6: Design, Deployment and Analysis - WINLAB · 1. Asset Tracking with Roll-Call. TM: Design, Deployment and Analysis. Yanyong Zhang, Ben Firner, Rich Howard, Wade Trappe. WINLAB, Rutgers

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Our Solution: Our Solution: Roll-CallTM

Active Tag:•

Tag periodically announces its ID.•

Receiver disabled.•

Life time: 1 year (3 V,220 mA-hr coin battery).

Basestation:•

Receives and timestamps the packets, then transfer them to the processing station

Multiple receives used to provide overlapping coverage.Central Processing Unit:•

Tracks the tags using data from multiple receivers.

Page 7: Design, Deployment and Analysis - WINLAB · 1. Asset Tracking with Roll-Call. TM: Design, Deployment and Analysis. Yanyong Zhang, Ben Firner, Rich Howard, Wade Trappe. WINLAB, Rutgers

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Challenges: Packet LossesChallenges: Packet LossesPacket losses can lead to false alarms.There are three types of losses:•

Ambient losses due to radio environment

Tag 7 had a loss ratio over 80%

Solution: better placement of basestations

Page 8: Design, Deployment and Analysis - WINLAB · 1. Asset Tracking with Roll-Call. TM: Design, Deployment and Analysis. Yanyong Zhang, Ben Firner, Rich Howard, Wade Trappe. WINLAB, Rutgers

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Challenges: Packet LossesChallenges: Packet LossesPacket losses can lead to false alarms.There are three types of losses:•

Ambient losses due to radio environment•

Collision lossesRandom transmissions lead to collisionsOur model shows that in a 100-tag system with each tag transmitting a 100 bit packet in 100ms epochs, the collision probability is 5%

Soln II: Varying Transmission Periods

A tag varies its transmission period

it won’t collide with the same set of tags repeatedly.

Soln I: Software Collision Prediction

Roll-call can predict the times for tag transmissions and collisions

If a corrupted packet is received, we know it is a collision!

Page 9: Design, Deployment and Analysis - WINLAB · 1. Asset Tracking with Roll-Call. TM: Design, Deployment and Analysis. Yanyong Zhang, Ben Firner, Rich Howard, Wade Trappe. WINLAB, Rutgers

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Challenges: Packet LossesChallenges: Packet LossesPacket losses can lead to false alarms.There are three types of losses:•

Ambient losses due to radio environment•

Collision losses•

Dead-time losses due to unavailability of the basestationProcessing timeTransfer time

Solution: Reduce the processing at the basestation, and buffering the packets for a batch transfer

Page 10: Design, Deployment and Analysis - WINLAB · 1. Asset Tracking with Roll-Call. TM: Design, Deployment and Analysis. Yanyong Zhang, Ben Firner, Rich Howard, Wade Trappe. WINLAB, Rutgers

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Throughput Limit TestThroughput Limit TestExperiment setup: a tag transmits 20,000 packets at different packet intervals

Combining buffering and use of multiple basestations achieves the best performance

Page 11: Design, Deployment and Analysis - WINLAB · 1. Asset Tracking with Roll-Call. TM: Design, Deployment and Analysis. Yanyong Zhang, Ben Firner, Rich Howard, Wade Trappe. WINLAB, Rutgers

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Raw Packet Loss RatioRaw Packet Loss Ratio

Number of basestations

Pack

et los

s (%

)

Page 12: Design, Deployment and Analysis - WINLAB · 1. Asset Tracking with Roll-Call. TM: Design, Deployment and Analysis. Yanyong Zhang, Ben Firner, Rich Howard, Wade Trappe. WINLAB, Rutgers

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Presence DetectionPresence DetectionRaw packet loss ratio information is not fed into applications; instead, we need to detect whether a tag is missingDeclare miss ratio (DMR)•

how resilient a detection scheme is against packet losses•

n packet losses, out of which we detect m tag misses, then the DMR is m/n

Report Latency (RL) •

The interval between the last when a tag was heard and the time it was declared missing given that it is actually lost

Detection Heuristicsmethod DMR (%) RL (rounds)Single Miss 100 1

Single Ambient Miss 1.47 1.33

5 ambient misses 0.0122 12.5

Max misses 0.0393 5.10

Max misses + 5 0.0034 23.3

Page 13: Design, Deployment and Analysis - WINLAB · 1. Asset Tracking with Roll-Call. TM: Design, Deployment and Analysis. Yanyong Zhang, Ben Firner, Rich Howard, Wade Trappe. WINLAB, Rutgers

Presence DetectionPresence Detection

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Page 14: Design, Deployment and Analysis - WINLAB · 1. Asset Tracking with Roll-Call. TM: Design, Deployment and Analysis. Yanyong Zhang, Ben Firner, Rich Howard, Wade Trappe. WINLAB, Rutgers

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Conclusions and Future DirectionsConclusions and Future DirectionsThe initial Roll-CallTM design is promisingPacket losses can be further reduced•

More enhancements are on the wayExtracting information from collided packetsEmploying basestations with multiple processors

More sophisticated detection algorithms are neededWill extensively study the performance in different environments

Page 15: Design, Deployment and Analysis - WINLAB · 1. Asset Tracking with Roll-Call. TM: Design, Deployment and Analysis. Yanyong Zhang, Ben Firner, Rich Howard, Wade Trappe. WINLAB, Rutgers

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Questions & AnswersQuestions & Answers