fairness matters: identification of active rfid tags with statistically guaranteed fairness michigan...

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

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000 001

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1

10 11

010 011 100 101

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1101

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101

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11 12

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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