Expecting the Unexpected: Fast and Reliable
Detection of Missing RFID Tags in the Wild
Muhammad Shahzad
Alex X. Liu
Dept. of Computer Science and Engineering
Michigan State University
East Lansing, Michigan, 48824, USA
Motivation
Shop Lifting
Employee Theft
2011: Retailers lost 34.5 billion USD
2
Problem Statement
 Input
─ Set of IDs of expected tags
─ RFID tag population containing:
● some or all expected tags
● unexpected tags
─ Threshold on number of missing tags, T
─ Required reliability, α ∈ [0,1)
 Objective
─ Detect the event: missing tags ≥ T
─ Event detection probability ≥ α
─ Minimize detection time
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Limitations of Prior Art
 Assume there are no unexpected tags
ICDCS 2008: How to monitor for missing RFID tags; Tan, Sheng, and Li
MobiHoc 2010: Identifying the missing tags in a large RFID system; Li, Sheng, and Lin
SECON 2011: Fast identification of the missing tags in a large RFID system; Zhang, Liu, and Sun
IEEE ToC 2013: Completely pinpointing the missing RFID tags in a time-efficient way; Liu et. al.
 However, in reality, there are unexpected tags
Airline baggage
Multi-tenant warehouse
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Naïve Solutions
 Identification protocol
─ Slow: fastest RFID identification protocol is 14.3 times slower
compared to our scheme
● SIGMETRICS 2013: Probabilistic Optimal Tree Hopping for RFID Identification;
Shahzad and Liu
 Estimation protocol
─ Inaccurate: if new tags join, can not tell whether some tags
went missing
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Communication Protocol Overview
1
2
3
4
5
6
7
0 1 1 C 0 1 1
Frame size 𝑓 = 7
Seed 𝑅
3
2
6
4
7
4
 Faster to distinguish between empty and non-empty slots
 Singleton and collision » non-empty
 At the end of frame, reader gets a sequence of 0s and 1s
─ 011C011 becomes 0111011
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RUN: Missing Tags Detection
1
1
Frame size 𝑓 = 11
Seed 𝑅
1
2
3
4
4
5
11
6
7
5
8
9
6
10
Expected tags to
be monitored
11
1 0 0 1 1 1 0 0 0
0 1
Pre-computed frame
1 0 0 1 0 1 0 1 0
1 1
Executed frame
Unexpected false
positive
Unexpected tag
detected
Missing tag event
detected
Unexpected tags
8
4
10
10
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RUN: Handling Unexpected FPs
Repeat frame 𝑛 times
1 0 0 1 1 1 0 0 0
0 1
1 0 0 1 1 1 0 1 0
1 1
1 1 0 0 0 1 1 0 0
0 0
1 1 0 1 0 1 1 1 0
0 1
0 1 1 0 0 0 1 0 0 1
0
0 1 0 1 1 0 1 0 0 1
0
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RUN: Parameter Selection
 Three unknown parameters
─ Frame size 𝑓
─ Number of frames 𝑛
─ Persistence probability 𝑝
 Two equations
─ 𝑓=
●
●
●
●
𝑝(𝑇−|𝐸|−|𝑈|)
ln{1−𝑞}−ln{𝑝}
where 𝑞 = (1 − α)1/𝑛𝑇
obtained using the expression of false positive probability
|𝐸| : number of expected tags
|𝑈| : number of unexpected tags
𝑞
𝑛𝑇(𝑞−1)
─ 𝑝 = (1 − 𝑞)(1 − α)
● Obtained using the required reliability condition
 Need the number of unexpected tags |𝑈|
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RUN: Estimating Unexpected Tags
1
1
1
2
3
8
4
4
5
4
11
6
7
10
5
8
9
6
10
11
10
 Number of total slots in frame 𝑓
 Number of grey slots in frame 𝑘
 Number of white slots that become green slots: 𝑁 01
𝑓
𝑁 01
𝑈 = − ln 1 −
𝑝
𝑓−𝑘
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RUN: Experimental Evaluation
 Implemented 4 protocols in addition to RUN
1.
2.
3.
4.
5.
TRP (ICDCS, 2008)
IIP (MobiHoc, 2010)
MTI (SECON, 2011)
SFMTI (IEEE ToC, 2013)
TH (SIGMETRICS, 2013)
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Actual Reliability vs. Missing Tags
 Number of expected tags = 1,000
 Number of unexpected tags = 10,000
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Actual Reliability vs. Unexpected Tags
 Number of expected tags = 1,000
 Number of missing tags = 200
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Effect of Threshold T




Number of expected tags = 1,000
Number of unexpected tags = 10,000
Threshold = 200
Required reliability = 0.99
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RUN vs. RFID Identification
 Compared RUN with TH (SIGMETRICS 2013)
 RUN is 14.3 times faster than TH for
─
─
─
─
Number of expected tags = 1,000
Number of unexpected tags = 10,000
Threshold = 200
Required reliability = 0.99
 TH is faster than RUN when
─ Required reliability > 0.99999, OR
─ Threshold < 0.001 tags, which is impossible
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Conclusion
 Proposed a protocol to reliably detect missing tags in
presence of unexpected tags
─
─
─
─
Reliable
Fast
C1G2 compliant
Handles multiple readers
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Questions?
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