Fairness Matters: Identification of Active RFID Tags with Statistically
Guaranteed Fairness
Michigan State UniversityMuhammad Shahzad Alex X. Liu
North Carolina State University
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Radio Frequency Identification
ActivePassive
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Active RFID Tags
Railways Seismology
Automotive Aircraft
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Tree Walking
0
00
000 001
01
1
10 11
010 011 100 101
100
0
100
1101
0
101
1
1
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3 4
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6 7
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9
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11 12
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14 15
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Problem Statement Input
─ RFID tag population of unknown size─ Required fairness = α
Output─ IDs of all tags─ Minimize identification time─ Achieved fairness ≥ α
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Interpreting Fairness Example:
─ Tag battery depletes after 100,000 transmissions─ One thousand identification rounds per day─ Fairness = 0.84
● 20% tags last for 33 days● 30% tags last for 50 days● 50% tags last for 100 days
─ Fairness = 0.99● 1% tags last for 50 days● 99% tags last for 100 days
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Communication Protocol Overview
e s s c e s s
3 2 6 4 47
1 2 3 4 5 6 7
e s s c e s s
Frame size fi = 7
Number of empty slots: ei
Number of successful slots: si
Number of collision slots: ci
the tunable parameter
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Proposed Approach
1. Estimate tag population size─ Using ART [MobiCom 2012]─ One time cost
2. Calculate optimal frame size and execute frame3. Re-estimate unidentified tag population size
─ Go to step 2
optimal frame size
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Jain’s Fairness Index xl = amount of resource used by lth node t = total number of nodes
Jain’s fairness index lies in the range [1/t, 1]
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Jain’s Fairness Index for Tags xl = number of times a tag with label l transmits t = total number of tags
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Jain’s Fairness Index for Tags
where
Smaller the load factor, higher the fairness
Trade-off time for fairness
load factor
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Identification Time
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Constraint Optimization Problem
Now we know load factor k We already know ti from re-estimation
We get fi , because k = ti/fi
Trading-off time for fairness
Just optimal Aloha
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Handling Large Frame Sizes Max allowed frame size = fmax
Divide population into 2z groups of equal size─ where, z = ceil(log2{fi / fmax})
Execute frames of size ceil(fi / 2z) Use SELECT command to make t / 2z tags
participate for each frame─ LSBs of tags are almost uniformly distributed
● Tags with IDs ending in 0 = Tags with IDs ending in 1
─ Example: to divide into four groups1. Use SELECT with 002. Use SELECT with 013. Use SELECT with 104. Use SELECT with 11
Proof of fairness for this method in paper
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Experimental Evaluation Implemented 9 protocols in addition to FRIP
1. BS (IEEE Trans. on Information Theory , 1979)2. ABS (MobiHoc, 2006)3. TW (DIAL-M 2000)4. ATW (Tanenbaum, 2002)5. STT (Infocom, 2009)6. MAS (PerCom, 2007)7. ASAP (ICDCS 2010)8. Frame Slotted Aloha (IEEE Transactions on
Communications, 2005)9. TH (MobiCom 2012)
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Fairness
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Identification Time
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Effect of Splitting Tag Population
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Comparison: Fairness
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Comparison: Time
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Conclusion First effort towards developing a fair RFID
identification protocol Proposed a method to achieve the required fairness
while minimizing identification time More in the paper
─ Formal proofs and derivations of various aspects─ More comparisons of FRIP with prior protocols