Energy-Conserving Access Protocols for Identification Networks By Imrich Chlamtac, Chiara Petrioli, and Jason Redi IEEE/ACM TRANSACTIONS ON NETWORKING, Feb CSE519 Embedded Networks Feb. 5, 2007 Su Jin Kim

Overviews Introduction Current Access Protocols Proposed Protocols Energy-Analysis Simulation Results Conclusion References

Introduction Radio Frequency Identification Devices (RFID) and Infrared Identification Devices (IRID)  Small, Inexpensive, resource-limited IDNET (IDentification NETwork)  Interconnected base stations  Large number of small low-cost wireless tags  Tags contain microprocessor power source, a RF receiver, transmitter, and some support logic. -> Active Tags

RFID Systems Examples: Location tracking of the animals, Supply chain, Health-Care etc. Characteristics  Scale: large  Cost: inexpensive  Size: small  Traffic: short, simple message → Important issues : Low Energy and Low Delay Requirements

Current Access Protocols (1) Low Power Design  awake & sleep state Random Access Protocol (Aloha)  The base stations send packets at random times  The tags awakes at random times  The probability of a tag and the base station being awake in the same slot is very low  High the energy consumption and packet delay

Current Access Protocols (2) Classical TDMA  Assign a time slot to each tag  Low energy requirement awake 1/N slots, N = # of tags in the system  High packet delay Trade-off: the energy vs. delay  How frequently does a tag awake?

Network Model N tags share a radio channel Packet-oriented and packet length is constant The time is slotted and the base station’s transmission is synchronized Exactly one packet can be transmitting during each slot Access Protocol  Transmission Scheduling: at the base station The base station selects a packet for transmission from the arrival queue in each slot  Wake-schedule: at each tag The tag determines the slots being awake

Grouped-Tag TDMA Protocols Divide tags into m =  N = # of tags in the system  X = # of tags in the group Assign each slot to one group Increase the average energy consumption per slot Decrease the average delay Drawbacks  Tags continue to wake up cyclically  The packets’ destination distribution is heavily clustered, the performance can degrade severely

Directory Protocols The base station 1. waits for k packets 2. Broadcast the directory which lists the destinations of the k packets 3. Transmit the actual packets Tags 1. listen to the directory and find out when they wake up 2. When there is no group being transmitted, the tags wake up periodically every v slots Trade-off  Small k, v: Low Delay, but High energy consumption  Large k, v: High Delay, but Low energy consumption

Pseudorandom Protocols All tags 1. run the same pseudorandom number generator, but each tag has the unique seed 2. Determine their state (awake or sleep) based on a probability p 3. Stored state of the random number generator The base station  Know the seeds of tags  Possible to determine the schedules of tags  Change p based on tags’ expected traffic rates Good for the heterogeneous traffic patterns

Energy Analysis (1) E: average percentage of slots in which a tag is awake Grouped-Tag TDMA Protocols  E =  m = # of the groups in the system =

Energy Analysis (2) Directory Protocols  E =  k = # of packets in the group k’ = the slots need for transmitting the directory Pseudorandom Protocol  E = p

Simulation Results 15,000 packets N = 1000 tags Inter-arrival rate,  I = 0.05, 0.2, 0.5 arrivals per slot

Classical Access Protocols * Random Access Only when p is high (> I), the system is stable * Classical TDMA Good Energy Consumption (0.001) Extremely Long Delay (≥500 slots)

Grouped-Tag TDMA with uniform destination distribution X = large High Energy Consumption Low Delay X = small Low Energy Consumption High Delay FINDING the OPTIMAL X is IMPORTANT!

Directory Protocol with uniform destination distribution k = large Low Energy Consumption High Delay With given k, v = large Low Energy Consumption High Delay FINDING the OPTIMAL k, v is IMPORTANT!

Pseudorandom Protocol with uniform destination distribution Slightly worse than the grouped-tag TDMA But, the difference decreases as I increases

Energy Conserving Protocols with I = 0.2

Energy Conserving Protocols with wide Gaussian Destination Distribution The performance of the grouped-tag TDMA degrades rapidly The performance of the pseudorandom degrades very slightly

Energy Conserving Protocols with narrow Gaussian Destination Distribution With I = 0.5, the performance of the grouped-tag TDMA is completely unstable

Conclusion Classical TDMA and Random (such as Aloha) Access Protocols are not appropriate for the RFID Systems Uniform Distribution Moderate Distribution Heavy Distribution Low traffic load Grouped-Tag TDMA Pseudorandom High traffic load Pseudorandom Directory

References “Energy-Conserving Access Protocols for Identification Networks,” I. Chlamtac, C. Petrioli, and J. Redi, IEEE/ACM Transactions on Networking, Vol. 7, No. 1, Feb “Analysis of Energy-Conserving Access Protocols for Wireless Identification Networks,” I. Chlamtac, C. Petrioli and J. Redi, the Proc. of Int. Conf. on Telecommunication System, March 20-23, 1997 “Extensions to the pseudo-random class of energy- conserving access protocols,” I. Chlamtac, C. Petrioli and J. Redi, the Proc. 2 nd IEEE Int. Workshop Wireless Factory Communication Systems, Oct. 1997, pp