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

BodyQoS: Adaptive and Radio-Agnostic QoS for Body Sensor Networks. IEEE INFOCOM 2008 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. Outline. Introduction and overview of BodyQoS

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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 IEEE INFOCOM 2008 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

  2. Outline • Introduction and overview of BodyQoS • VMAC Design • QoS Scheduler Design • Admission Control Design • Performance Evaluation • Conclusion

  3. Introduction and overview of BodyQoS • 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;

  4. Hurricane Katrina Relief

  5. 911 Terrorist Attack

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

  7. 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

  8. 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

  9. BodyQoS Contributios • Radio-Agnostic QoS • The Virtual MAC design allows the QoS system to be ported from one radio platform to another • Testbed Implementation • Implemented in TinyOS and evaluated on the MicaZ(XBOW)

  10. 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 BodyQoS

  11. VMAC Design

  12. VMAC Design Tinterval

  13. VMAC Design Npkt 13

  14. VMAC Design Spkt 14

  15. VMAC Design Tpkt 15

  16. VMAC Design TmaxPkt 16

  17. VMAC Design TminSleep 17

  18. VMAC Design BWeffective Delivered Bytes / Actual Time 18

  19. QoS Scheduler Design • Three types of traffic • Reserved aggregator  mote • Reserved mote  aggregator • Best-effort communication • Delay sensitivity • Low sensitivity: Avg-Tinterval/2 • High sensitivity: Avg-Tinterval/(2KmaxFre)

  20. QoS Scheduler Design • Mote  aggregator Qos reservation • The aggregator generates polling packets to poll each sensor mote for data within each time interval. • Dynamically configurable parameter PL (set the maximum number of packets requested within a single polling packet) • Sleep period Tsleep is piggybacked in each polling packet to notify corresponding sensor motes.

  21. QoS Scheduler Design • Measuring effective bandwidth • CODA (Congestion Detection and Avoidance in Sensor Networks ) • IEEE 802.11b RTS-CTS-DATA-ACK • VMAC send/receive Di packets within time Ti X Di, where Ti is the time for MAC to send a packet. • The aggregator waits the mote responds for Ti X Di +TmaxPkt

  22. QoS Scheduler Design • BWeffective=(Di*Bytes per Packet + Polling Packet size )/TwaitTime • BWeffective=(Num of Received Packets*Bytes per Packet + Polling Packet size )/(Ti X Di +TmaxPkt) • Polling packet was lost, BWeffective=0 • BWeffective= BWideal*(Num of Delivered Packet/Num of Request Packet)

  23. QoS Scheduler Design • BWideal= (Npkt*Spkt*8)/Tinterval • BWmovAvg ( i+1) =δ* BWeffective+(1-δ) *BWmovAvg ( i )

  24. QoS Scheduler Design • Advanced scheduling algorithms • RSVP-Light QoS Scheduling: An audio / video stream reservation consist of a fixed bandwidth and time for data communication. • Adaptive QoS Scheduling: Different with TCP, the lost packets should receive more opportunities to be retransmitted, and it is important to decide how much time for lost packets for retransmissions.

  25. QoS Scheduler Design • RSVP-Light QoS Scheduling • Di= (bi* Tinterval )/(Spkt * 8) • Ti = TminPkt • For VMAC to send out Di packets, BodyQoS should reserve a time period of TminPkt * Di • For high delay sensitivity, we modify Di= max{[(bi* Tinterval )/(Spkt * 8)], KmaxFre }

  26. Per Packet Trans. Time: # Requested Packets: QoS Scheduler Design • Adaptive QoS Scheduling Max. MAC Retrans. Time H H Interference Interference 26

  27. Admission Control Design • For aggregator  mote Qos reservation, no polling packets are needed. DAM =Σ Di, where Di= (bi* Tinterval )/(Spkt * 8) • For mote aggregator with low delay sensitivity: DMAL = Σ Di • For mote aggregator with high delay: DMAH = Σ max {Di, KmaxFre} • P(Polling overhead)= KFre{[(DMAL+DMAH)/ KFre]/PL}

  28. Admission Control Design • Admission Decisions • KH, KL are set within the source range[0,1] • New Qos request priority> all admitted Qos requests priorities and total bandwidth < KL *BWmovAvg

  29. Admission Control Design • New Qos request priority> all admitted Qos requests priorities and total bandwidth > KL *BWmovAvg • Low priority  High priority, High bandwidth requirement Low bandwidth requirement

  30. Admission Control Design • Bandwidth of all QoS reservations to be removed, including current one to be checked>bandwidth to be reclaimed the current reservation is ignored and go checking next. • Bandwidth of all QoS reservations to be removed, including current one to be checked<bandwidth to be reclaimed the current reservation is removed and go checking next.

  31. Admission Control Design • Bandwidth of all QoS reservations to be removed, including current one to be checked=bandwidth to be reclaimed the current reservation is removed and stop.

  32. 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

  33. 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 Implementation

  34. 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 Implementation • 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 Aggregator Side

  35. 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 Implementation • 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 35

  36. Conclusion • Asymmetric architecture • VMAC is developed in BodyQoS to make it radio-agnostic. • Adopts an adaptive scheduling strategy during times of channel impairment (RF interference or body fading) • Future work: co-existence body sensor network, and develop a new transport protocol.

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