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BodyQoS: Adaptive and Radio-Agnostic QoS for Body Sensor Networks

BodyQoS: Adaptive and Radio-Agnostic QoS for Body Sensor Networks. Gang Zhou College of William and Mary Jian Lu University of Virginia Chieh-Yih Wan, Mark D. Yarvis Intel Research John A. Stankovic University of Virginia. IEEE INFOCOM 2008. Hurricane Katrina Relief.

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BodyQoS: Adaptive and Radio-Agnostic QoS for Body Sensor Networks

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  1. BodyQoS: Adaptive and Radio-Agnostic QoS for Body Sensor Networks Gang Zhou College of William and Mary Jian Lu University of Virginia Chieh-Yih Wan, Mark D. Yarvis Intel Research John A. Stankovic University of Virginia IEEE INFOCOM 2008

  2. Hurricane Katrina Relief

  3. 911 Terrorist Attack

  4. Health Monitoring During Emergency Manual tracking of patient status, based on papers and phones, is the past; Real-time & continuous monitoring, through body sensor networks, is the future;

  5. Sweat Temp. A Typical Body Sensor Network Limb motion & muscle activity Heart rate & blood oxygen saturation Two-Lead EKG

  6. EKG Light Sweat Quality of Service for Body Sensor Networks • BodyQoS Goals • Priority-based admission control • Wireless resource scheduling • Providing effective bandwidth • Design Constraints • Heterogeneous resources • Heterogeneous radio platforms Data Control

  7. BodyQoS Contributios • The first Running QoS System for Body Sensor Networks • Asymmetric Architecture • Most work for the aggregator • Little work for sensor nodes • Virtual MAC • Separate QoS scheduling from underlying real MAC • Easy to port to different radio platforms • Effective BW Allocation • Adaptive resource scheduling, so that statistically the delivered BW meets QoS requirements, even during interference

  8. Decide which streams to serve and which not to serve • Schedule wireless resources • Calculate effective bandwidth • Put radio to sleep • Abstract wireless resource for QoS scheduling • Implemented by calling real MAC’s functions Poll Data • Asymmetric Architecture • Virtual MAC • Effective BW Allocation Asymmetric Architecture BodyQoS

  9. Asymmetric Architecture • Virtual MAC • Effective BW Allocation Wireless Resource Abstraction

  10. Asymmetric Architecture • Virtual MAC • Effective BW Allocation Wireless Resource Abstraction Tinterval

  11. Asymmetric Architecture • Virtual MAC • Effective BW Allocation Wireless Resource Abstraction Npkt

  12. Asymmetric Architecture • Virtual MAC • Effective BW Allocation Wireless Resource Abstraction Spkt

  13. Asymmetric Architecture • Virtual MAC • Effective BW Allocation Wireless Resource Abstraction Tpkt

  14. Asymmetric Architecture • Virtual MAC • Effective BW Allocation Wireless Resource Abstraction TmaxPkt

  15. Asymmetric Architecture • Virtual MAC • Effective BW Allocation Wireless Resource Abstraction TminSleep

  16. Asymmetric Architecture • Virtual MAC • Effective BW Allocation Virtual MAC Operation BWeffective Delivered Bytes / Actual Time

  17. Asymmetric Architecture • Virtual MAC • Effective BW Allocation Effective BW Allocation The ideal case: no Interference The general case: when interference is present If application requests BW bi, BodyQoS allocates BW bi That is, in each interval Tinterval, QoS scheduler requests VMAC to send/receiveDi packets within time Ti=Di*Tpkt Minimum per packet transmission time Interval length Packet size

  18. Per Packet Trans. Time: # Requested Packets: • Asymmetric Architecture • Virtual MAC • Effective BW Allocation Effective BW Allocation The general case: when interference is present Max. MAC Retrans. Time H H Interference Interference

  19. Implemented at Intel with Imote2 • Ported to MicaZ at UVA Explicit Noise Location EKG Temperature Adaptive QoS RTP-Like QoS Best effort Aggregator Data Collection Performance Evaluation Setup

  20. Adaptive QoS always delivers requested BW Delivered BWs for RTP-Like QoS and best-effort reduce when interference increase RTP-like QoS has better performance than best-effort Noise Node On 25ms per packet Noise Node On 20ms per packet Noise Node Off Noise Node On 30ms per packet 0s 225s 315s 400s 135s Performance

  21. Conclusions • We designed, implemented, and evaluated the first Running QoS System for Body Sensor Networks • Asymmetric Architecture • Most work for the aggregator • Little work for sensor nodes • Virtual MAC • Separate QoS scheduling from underlying real MAC • Easy to port to different radio platforms • Effective BW Allocation • Adaptive resource scheduling, so that statistically the delivered BW meets QoS requirements, even during interference • For more information, visit: www.cs.wm.edu/~gzhou

  22. The End

  23. Per Packet Trans. Time: # Requested Packets: • Asymmetric Architecture • Virtual MAC • Effective BW Allocation Effective BW Allocation The general case: when interference is present Max. MAC Retrans. Time H H Interference Interference

  24. Implemented at Intel with Imote2 • Ported to MicaZ at UVA • Ported to Telos at W&M 1:17 1:4 The same Implementation Most Work Done at the Aggregator

  25. Adaptive QoS always delivers requested BW Delivered BWs for RTP-Like QoS and best-effort reduce when interference increase RTP-like QoS has better performance than best-effort Noise Node On 25ms per packet Noise Node On 20ms per packet Noise Node Off Noise Node On 30ms per packet 0s 225s 315s 400s 135s Evaluation -- Bandwidth Delivery Ratio Aggregator Side

  26. Noise Node On 25ms per packet Noise Node On 20ms per packet Noise Node Off Noise Node On 30ms per packet 0s 225s 315s 400s 135s Evaluation -- Data Buffer Fetching Speed • Adaptive QoS always maintains 4Kbps fetching speed • Fetching speeds of RTP-Like QoS and best-effort reduce when interference is present • Fetching speed of RTP-like QoS is higher than that of best-effort Mote Side

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