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. College of William and Mary Hurricane Katrina Relief 2

3. College of William and Mary 911 Terrorist Attack 3

4. College of William and Mary 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. College of William and Mary A Typical Body Sensor Network Heart rate & blood oxygen saturation Two-Lead EKG Limb motion & muscle activity Sweat Temp.

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

7. College of William and Mary 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. College of William and Mary 8 Asymmetric Architecture Poll Data BodyQoS (1)Schedule wireless resources (2)Calculate effective bandwidth (3)Put radio to sleep (1)Abstract wireless resource for QoS scheduling (2)Implemented by calling real MAC’s functions ① Asymmetric Architecture ② Virtual MAC ③ Effective BW Allocation (1)Decide which streams to serve and which not to serve

9. College of William and Mary 9 Wireless Resource Abstraction T interval N pkt S pkt T Pkt T maxPkt T minSleep ① Asymmetric Architecture ② Virtual MAC ③ Effective BW Allocation

10. College of William and Mary 10 Wireless Resource Abstraction N pkt S pkt T Pkt T maxPkt T minSleep The length of each interval T interval ① Asymmetric Architecture ② Virtual MAC ③ Effective BW Allocation

11. College of William and Mary 11 Wireless Resource Abstraction T interval N pkt S pkt T Pkt T maxPkt T minSleep The maximum number of packets QoS Scheduler can send/receive within each interval, if there is no interference N pkt ① Asymmetric Architecture ② Virtual MAC ③ Effective BW Allocation

12. College of William and Mary 12 Wireless Resource Abstraction T interval N pkt S pkt T Pkt T maxPkt T minSleep The effective data payload size in each packet that can carry application data S pkt ① Asymmetric Architecture ② Virtual MAC ③ Effective BW Allocation

13. College of William and Mary 13 Wireless Resource Abstraction T interval N pkt S pkt T Pkt T maxPkt T minSleep The minimum time needed to send out a packet, if there is no interference T pkt ① Asymmetric Architecture ② Virtual MAC ③ Effective BW Allocation

14. College of William and Mary 14 Wireless Resource Abstraction T interval N pkt S pkt T Pkt T maxPkt T minSleep The maximum time needed to send out a packet or finally report giving up, if it suffers maximum backoffs/retransmissions T maxPkt ① Asymmetric Architecture ② Virtual MAC ③ Effective BW Allocation

15. College of William and Mary 15 Wireless Resource Abstraction T interval N pkt S pkt T Pkt T maxPkt T minSleep The minimum time for putting radio to sleep, which includes the sleeping/activation switch time and also considers the energy cost; T minSleep ① Asymmetric Architecture ② Virtual MAC ③ Effective BW Allocation

16. College of William and Mary 16 Virtual MAC Operation Delivered Bytes / Actual Time BW effective ① Asymmetric Architecture ② Virtual MAC ③ Effective BW Allocation

17. College of William and Mary 17 If application requests BW b i, BodyQoS allocates BW b i ① Asymmetric Architecture ② Virtual MAC ③ Effective BW Allocation Minimum per packet transmission time Packet size Interval length The ideal case: no Interference That is, in each interval T interval, QoS scheduler requests VMAC to send/receive D i packets within time T i =D i *T pkt The general case: when interference is present Effective BW Allocation

18. College of William and Mary 18 Interference Max. MAC Retrans. Time H Interference H ① Asymmetric Architecture ② Virtual MAC ③ Effective BW Allocation The general case: when interference is present Per Packet Trans. Time: # Requested Packets: Effective BW Allocation

19. College of William and Mary 19 EKGLocation Aggregator Adaptive QoS Best effort Explicit Noise Data Collection Temperature RTP-Like QoS Performance Evaluation Setup Implemented at Intel with Imote2Ported to MicaZ at UVA

20. College of William and Mary 20 Performance ① Adaptive QoS always delivers requested BW ② Delivered BWs for RTP-Like QoS and best-effort reduce when interference increase ③ RTP-like QoS has better performance than best-effort 135s 0s225s315s400s Noise Node Off Noise Node On 30ms per packet Noise Node On 25ms per packet Noise Node On 20ms per packet

21. College of William and Mary 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. College of William and Mary The End 22

23. College of William and Mary 23 Interference Max. MAC Retrans. Time H Interference H ① Asymmetric Architecture ② Virtual MAC ③ Effective BW Allocation The general case: when interference is present Per Packet Trans. Time: # Requested Packets: Effective BW Allocation

24. College of William and Mary 24 Implementation Implemented at Intel with Imote2Ported to MicaZ at UVA 1:17 Most Work Done at the Aggregator 1:4 The same VMAC<100 lines of code BodyQoS~3700 lines of code Only need to modify VMAC Easy to Port to Different Radio Platforms Ported to Telos at W&M

25. College of William and Mary 25 Evaluation -- Bandwidth Delivery Ratio ① Adaptive QoS always delivers requested BW ② Delivered BWs for RTP-Like QoS and best-effort reduce when interference increase ③ RTP-like QoS has better performance than best-effort Aggregator Side 135s 0s225s315s400s Noise Node Off Noise Node On 30ms per packet Noise Node On 25ms per packet Noise Node On 20ms per packet

26. College of William and Mary 26 Evaluation -- Data Buffer Fetching Speed ① Adaptive QoS always maintains 4Kbps fetching speed ② Fetching speeds of RTP-Like QoS and best-effort reduce when interference is present ③ Fetching speed of RTP-like QoS is higher than that of best-effort Mote Side 135s 0s225s315s400s Noise Node Off Noise Node On 30ms per packet Noise Node On 25ms per packet Noise Node On 20ms per packet