Cardinality estimation for large scale rfid systems
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Cardinality Estimation for Large-scale RFID Systems. Chen Qian , Hoilun Ngan, and Yunhao Liu Hong Kong University of Science and Technology. RFID: Hot Topic. Both in industry and academic society RFID: independent sessions (three or more papers) in PerCom 2007, 2008 2009?.

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Cardinality estimation for large scale rfid systems

Cardinality Estimation for Large-scale RFIDSystems

Chen Qian, Hoilun Ngan, and Yunhao Liu

Hong Kong University of Science and Technology


Rfid hot topic
RFID: Hot Topic

  • Both in industry and academic society

  • RFID: independent sessions (three or more papers) in PerCom 2007, 2008

  • 2009?


Research issues take our group as an example
Research Issues(take our group as an example)

  • Localization

  • Object Tracking

  • Security & Privacy

  • Tag Counting & Estimation

To be expanded…


Rfid hot topic1
RFID: Hot Topic

  • Some RFID papers in other top confs.

M. S. Kodialam, T. Nandagopal, “Fast and reliable estimation schemes in RFID systems”, MobiCom 2006

J. Myung, W. Lee, “Adaptive splitting protocols for RFID tag collision arbitration”, MobiHoc 2006

Z. Zhou, et. al., "Slotted Scheduled Tag Access in Multi-Reader RFID Systems", ICNP 2007

Qunfeng Dong, et. al., “Load Balancing in Large-Scale RFID Systems”, Infocom 2007


Rfid sys model
RFID Sys. Model

RFID Readers

  • Carrying antennas, collect info from nearby tags.

  • Connected with servers

RFID Tags

  • Labeled with unique serial #s

  • Simple structure

  • Large-deployed, but can not communicate with each other

If multiple tags transmit to reader simultaneously, a collision happens, and reader cannot recognize these tags.


Real problems
Real Problems

  • RFID tags are used to label large-volume items.

  • Hence, collecting the information of these items is the main goal of the RFID system.

  • Two main kinds of information:

    • Identities Cardinality

Identification

Counting


Tag counting some applications
Tag counting:Some applications

  • Hong Kong International Airport

Cargo transportations


Tag counting some applications1
Tag counting:Some applications

  • Stadium RFID System

Security and traffic control


Identification limitation
Identification:Limitation

  • We can obtain the tag cardinality via identification.

    But….

    Extremely long latency

    • 1000 sec for 3000 tags

      Not applicable for mobile objects


Estimation mobicom 06
Estimation(Mobicom 06)


Estimation limitation
Estimation:Limitation

  • Multiple-reading problem


Our goal
Our Goal

  • Design an estimation scheme that can

    • Eliminate replications from the sum of reader results.

    • Achieve a short processing time,

    • And high accuracy.


LPE

  • Linear Probabilistic Estimation (LPE)

Replication-insensitive


Lpe limitation
LPE:Limitation

  • Processing time is still too long to be ideal

  • One can never know in advance that how long the ALOHA frame should be set.


Can we design an estimation scheme

that works well without pre-knowledge?



Gd galton board
GD Galton Board

Geometric Distribution


LoF

  • Lottery Frame

Approximately

1/2(t+1)of the tag responses are in time slot t.


LoF

The kth bit in bitmap BM[k] will be zero if k>>log2n, or be one if k<<log2n.

The fringe consists zeros and ones for the k whose value is near log2n.

R is the position of the right most zero


LoF

P. Flajolet and G. N. Martin, "Probabilistic Counting Algorithms for Data Base Applications," Journal of Computer and System Science, vol. 31, 1985.


Lof accuracy
LoF:accuracy

  • LoF estimation may not be accurate enough for some applications.

  • Luckily the right most zero R is an unbiased estimator of log2n, which means

If we make several independent estimations and compute the average result, the standard error will be reduced.


Lof multiple hashes
LoF:multiple hashes

Consider the average value

The variable has the expectation and standard deviation that satisfy

Therefore, the improved estimator is


Lof accuracy1
LoF:accuracy


Lof processing time
LoF:processing time

The number of time slots required

for a frame is independent from the

size of tag set.

A frame with 16 slots is enough to

estimate up to 216 = 65536 tags.


Simulation setup
Simulation:setup

Fixed 32-slot length for LoF estimation.


Simulation single reader
Simulation:Single reader


Simulation single reader1
Simulation:Single reader


Simulation multiple reader
Simulation:Multiple reader


Simulation processing time
Simulation:Processing time

Just the last time!


Summary
Summary

  • LoF is a replication-insensitive estimation, working well in multi-reader environments.

  • LoF can obtain higher accuracy and lower latency, comparing with previous schemes.

  • Trade-off in LoF: the storage for hash functions.



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