Every Bit Counts – Fast and Scalable RFID Estimation Muhammad Shahzad and Alex X. Liu Dept. of...
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Transcript of Every Bit Counts – Fast and Scalable RFID Estimation Muhammad Shahzad and Alex X. Liu Dept. of...
![Page 1: Every Bit Counts – Fast and Scalable RFID Estimation Muhammad Shahzad and Alex X. Liu Dept. of Computer Science and Engineering Michigan State University.](https://reader038.fdocuments.net/reader038/viewer/2022110321/56649cfa5503460f949cbe36/html5/thumbnails/1.jpg)
Every Bit Counts – Fast and Scalable RFID Estimation
Muhammad Shahzad and Alex X. LiuDept. of Computer Science and Engineering
Michigan State UniversityEast Lansing, Michigan, 48824
USA
![Page 2: Every Bit Counts – Fast and Scalable RFID Estimation Muhammad Shahzad and Alex X. Liu Dept. of Computer Science and Engineering Michigan State University.](https://reader038.fdocuments.net/reader038/viewer/2022110321/56649cfa5503460f949cbe36/html5/thumbnails/2.jpg)
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Radio Frequency Identification
Mobicom 2012
Chip
Antenna
ActivePassive
![Page 3: Every Bit Counts – Fast and Scalable RFID Estimation Muhammad Shahzad and Alex X. Liu Dept. of Computer Science and Engineering Michigan State University.](https://reader038.fdocuments.net/reader038/viewer/2022110321/56649cfa5503460f949cbe36/html5/thumbnails/3.jpg)
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Radio Frequency Identification
Mobicom 2012
![Page 4: Every Bit Counts – Fast and Scalable RFID Estimation Muhammad Shahzad and Alex X. Liu Dept. of Computer Science and Engineering Michigan State University.](https://reader038.fdocuments.net/reader038/viewer/2022110321/56649cfa5503460f949cbe36/html5/thumbnails/4.jpg)
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RFID Estimation
Exact IDs can not be read due to privacy requirements
Mobicom 2012
Exact IDs are not required but only a count
Identification protocols can use the count to speed up identification process
![Page 5: Every Bit Counts – Fast and Scalable RFID Estimation Muhammad Shahzad and Alex X. Liu Dept. of Computer Science and Engineering Michigan State University.](https://reader038.fdocuments.net/reader038/viewer/2022110321/56649cfa5503460f949cbe36/html5/thumbnails/5.jpg)
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Problem Statement Input
─ Confidence interval β ∈ (0,1]─ Required Reliability α ∈ [0,1)
Output─ An estimate te of tag population size t such that
● 1-β ≤ te / t ≤ 1+β
● P{ 1-β ≤ te / t ≤ 1+β } ≥ α
Mobicom 2012
![Page 6: Every Bit Counts – Fast and Scalable RFID Estimation Muhammad Shahzad and Alex X. Liu Dept. of Computer Science and Engineering Michigan State University.](https://reader038.fdocuments.net/reader038/viewer/2022110321/56649cfa5503460f949cbe36/html5/thumbnails/6.jpg)
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Additional Requirements Single Reader environment Multiple reader environment with overlapping
regions C1G2 standard compliant tags Active tags and Passive tags Scalable
Mobicom 2012
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Why do we need a new protocol? Non compliance with C1G2 standard Non-scalable Inability to achieve required reliability Room for improvement in speed
Mobicom 2012
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Communication Protocol Overview
Mobicom 2012
0 1 1 C 0 1 1
frame size f =73 2 6 4 47
Faster to distinguish between empty and non-empty slots Slower to distinguish between empty, singleton, and collision Singleton and collision » non-empty At the end of frame, reader gets a sequence of 0s and 1s
─ 011C011 becomes 0111011
1 2 3 4 5 6 7
0 1 1 C 0 1 1
![Page 9: Every Bit Counts – Fast and Scalable RFID Estimation Muhammad Shahzad and Alex X. Liu Dept. of Computer Science and Engineering Michigan State University.](https://reader038.fdocuments.net/reader038/viewer/2022110321/56649cfa5503460f949cbe36/html5/thumbnails/9.jpg)
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Estimation Any measure which is a
monotonous function of t can be used for estimation─ Number of 1s in a frame─ Number of 0s in a frame
Any measure which is a monotonous function of t can be used for estimation─ Number of runs of 1s─ Number of runs of 0s
Any measure which is a monotonous function of t can be used for estimation─ Average run size of 1s─ Average run size of 0s
1 13 25 37 49 61 73 85 97 1091211331451571691811930
2
4
6
8
10
12
Number of Tags
Ave
rage
ru
n s
ize
of 0
s
1 13 25 37 49 61 73 85 97 1091211331451571691811930
2
4
6
8
10
12
14
16
Number of Tags
Nu
mb
er o
f 0s
1 13 25 37 49 61 73 85 97 1091211331451571691811930
0.5
1
1.5
2
2.5
3
3.5
4
4.5
Number of Tags
Nu
mb
er o
f ru
ns
of 0
s
Mobicom 2012
1 13 25 37 49 61 73 85 97 1091211331451571691811930
2
4
6
8
10
12
14
16
18
Number of Tags
Ave
rage
ru
n s
ize
of 1
s
1 13 25 37 49 61 73 85 97 1091211331451571691811930
0.5
1
1.5
2
2.5
3
3.5
4
4.5
Number of Tags
Nu
mb
er o
f ru
ns
of 1
s
1 13 25 37 49 61 73 85 97 1091211331451571691811930
2
4
6
8
10
12
14
16
18
Number of Tags
Nu
mb
er o
f 1s
011100 0 111 00
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Useable Measures
Mobicom 2012
Average run size of 1s
0 50 100 1500
5
10
15
20
Number of tags t
Aver
age
size
of ru
ns1s0s
101
102
10�1
100
101
102
103
Number of tags t
Varia
nce
Size of first run of 0sTotal 0sTotal 1sRuns of 1sRuns of 0sAvg. run size
Number of 1s Number of 0s Number of runs of 1s Number of runs of 0s Average run size of 1s Average run size of 0s
![Page 11: Every Bit Counts – Fast and Scalable RFID Estimation Muhammad Shahzad and Alex X. Liu Dept. of Computer Science and Engineering Michigan State University.](https://reader038.fdocuments.net/reader038/viewer/2022110321/56649cfa5503460f949cbe36/html5/thumbnails/11.jpg)
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ART Protocol
Mobicom 2012
0 1 1 1 0 1 1
frame size f = 73 2 6 4 47
1 2 3 4 5 6 7
0 1 1 1 0 1 1
Repeat frames n times
Calculate avg. run size of 1s from n frames
Number of Tags
Ave
rage
ru
n s
ize
of 1
s
Obtain the estimate
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Scalability Problem
Mobicom 2012
0 0 01 1 1 1C C C CC C CC
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Scalability Problem Addressed
Mobicom 2012
0 01 C
Use persistence probability p
frame size f = 4/p = 16
= 0.25
8 3 16 1211
2 5 3 12 79
5
Obtain the estimate using information from this frame
Tags follow a uniform distribution Extrapolate with the factor of p
![Page 14: Every Bit Counts – Fast and Scalable RFID Estimation Muhammad Shahzad and Alex X. Liu Dept. of Computer Science and Engineering Michigan State University.](https://reader038.fdocuments.net/reader038/viewer/2022110321/56649cfa5503460f949cbe36/html5/thumbnails/14.jpg)
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10 20 30 40 50400
500
600
700
800
Frame size f
f n
Optimization The expression for number of rounds n depends on
─ Confidence interval β─ Required Reliability α─ Frame size f
n = func(α, β, f )
Mobicom 2012
Estimation time ∝ f × n─ d/df (f ×n ) = 0
Two equations1. n = func(α, β, f )2. d/df (f ×n ) = 0
Two unknowns1. Number of rounds n 2. Frame size f
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Multiple Readers Environment First proposed by Kodialam et. al. in “Anonymous
tracking using RFID tags”
Mobicom 2012
frame size f = 4
f =4
R
f =4
R
2
2
3
11
1 0 1 01 1 1 0
Seed RSeed R
Logical
OR1 0 1 01 1 1 0 1 1 1 0
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Advantages of ART over prior art Speed:
─ 7 times faster than fastest ● β = 0.1%, α = 99.9%
Deployability─ Does NOT require modifications to
● tags ● communication protocol
Mobicom 2012
![Page 17: Every Bit Counts – Fast and Scalable RFID Estimation Muhammad Shahzad and Alex X. Liu Dept. of Computer Science and Engineering Michigan State University.](https://reader038.fdocuments.net/reader038/viewer/2022110321/56649cfa5503460f949cbe36/html5/thumbnails/17.jpg)
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Performance Evaluation
Mobicom 2012
103
104
105
1060
50
100
150
200
250
Number of tags t
Estim
atio
n tim
e (s
ec)
FNEBMLEEZBUPEART
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Performance Evaluation
Mobicom 2012
0 0.02 0.04 0.06 0.08 0.1
100
102
104
Confidence Interval
Estim
atio
n tim
e (s
ec)
FNEBMLEEZBUPEART
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Performance Evaluation
Mobicom 2012
0.9 0.92 0.94 0.96 0.98 10
50
100
150
Required reliability
Estim
atio
n tim
e (s
ec)
FNEBMLEEZBUPEART
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Conclusion New estimator: the average run size of 1s Faster than existing estimation schemes
─ smaller variance Single and multiple reader environment C1G2 standard compliant tags Active tags and Passive tags Scalable: independent of tag population size
Mobicom 2012
![Page 21: Every Bit Counts – Fast and Scalable RFID Estimation Muhammad Shahzad and Alex X. Liu Dept. of Computer Science and Engineering Michigan State University.](https://reader038.fdocuments.net/reader038/viewer/2022110321/56649cfa5503460f949cbe36/html5/thumbnails/21.jpg)
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Questions?
Mobicom 2012