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Delivery ratio-maximized wakeup scheduling for ultra-low duty-cycled WSNs under real-time constraints Fei Yang, Isabelle Augé-Blum National Institute of.

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Presentation on theme: "Delivery ratio-maximized wakeup scheduling for ultra-low duty-cycled WSNs under real-time constraints Fei Yang, Isabelle Augé-Blum National Institute of."— Presentation transcript:

1 Delivery ratio-maximized wakeup scheduling for ultra-low duty-cycled WSNs under real-time constraints Fei Yang, Isabelle Augé-Blum National Institute of Applied Sciences of Lyon in the Telecommunications department ( 法國里昂國立應用科學學院 ) Computer Networks 2011 898410120 陳正昌 2011/03/28

2 Page: 2 WMNL Performance Evaluation Introduction and Goals Wakeup Scheduling Algorithm Conclusions

3 Page: 3 WMNL Performance Evaluation Introduction and Goals Wakeup Scheduling Algorithm Conclusions

4 Page: 4 WMNL WSNs have been widely used in many applications. The data flows of WSN applications can be mainly classified into four types –Event-driven –Query-driven –Continuous –Hybrid

5 Page: 5 WMNL The characteristics of event-driven WSN applications are –Not have data most of the time –Have to report to the sink with real-time constraints Nodes spend most of the time on idle listening.

6 Page: 6 WMNL Typical power consumptions for an IEEE 802.15.4 radio (CC2420). –Transmit ： 52.2 mW –Receive ： 56.4 mW –Listen ： 56.4 mW –Sleep ： 3  W Sensor nodes are battery-powered –Energy saving is an important issue in WSNs.

7 Page: 7 WMNL Duty-cycled approach can prolongs the sensor lifetime. … Time Scheduling period

8 Page: 8 WMNL Duty-cycle will negatively affect other performances –End-to-end delay –Connectivity Although some existing scheduling algorithms can reduce the end-to- end delay –Didn’t takes routing into account –Didn’t have a bounded delay –Didn’t takes unreliable links into account

9 Page: 9 WMNL Proposes a novel forwarding scheme for ultra-low duty-cycle WSNs. –Improve the energy efficiency –Decrease end-to-end delay –Increase delivery ratio –Guarantee bounded delay on the messages –Distributed scheduling

10 Page: 10 WMNL Performance Evaluation Introduction and Goals Wakeup Scheduling Algorithm Conclusions

11 Page: 11 WMNL … Time All nodes are locally synchronized with their neighbors. Only one node sends the alarm when the event happens. One duty-cycle period is divided into many slots and have same duration. Each node wakes up for only one slot during one period. The node can wake up for more than one slot when it has packets to send. B B B B B B A A A A A A

12 Page: 12 WMNL Sink … Time … 31 slots Slots 1~5 Slots 6~10 Slots 11~15 Slots 16~20 Slots 21~25 Slots 26~30 Slot 31 0.9 0.8 0.7 0.6 0.5 Slot 1 Slot 2 Slot 3 Slot 4 Slot 5 Expected Delivery Ratio

13 Page: 13 WMNL

14 Page: 14 WMNL ∞∞ D D A A B B Sink C C α=0.5 0.9 0.8 0.3 0.8 0.6 1 0 1 3 2 ∞ ∞

15 Page: 15 WMNL D D A A B B Sink C C 0.7 0.4 0.6 0.7 0.8 100 95 94 93 π(F D )={B, C, A} EDR(π(F D ))= 0.6*0.4 +(1-0.6)*0.7*0.6 +(1-0.6)*(1-0.7)*0.8*0.7 =0.4752

16 Page: 16 WMNL D D A A B B Sink C C 0.7 0.4 0.6 0.7 0.8 100 93 94 95 π(F D )={A, C, B} EDR(π(F D ))= 0.8*0.7 +(1-0.8)*0.7*0.6 +(1-0.8)*(1-0.7)*0.6*0.4 =0.6584 > 0.4752

17 Page: 17 WMNL Expected Delivery Ratio (EDR) Hop Count (HC) … Time … T

18 Page: 18 WMNL Expected Delivery Ratio (EDR) Hop Count (HC) 0~1

19 Page: 19 WMNL Wakeup Slot (WS) Selection Sink HC=1HC=2HC=3HC=4HC=5HC=6 HC upbound =6 54 slots … Time 0 8 9 17 18 26 27 35 36 44 45 53

20 Page: 20 WMNL Wakeup Slot (WS) Selection Sink B B C C A A HC=5HC=6 HC upbound =6 54 slots … Time 0 8 9 17 18 26 27 35 36 44 45 53 EDR C =0.6 EDR B =0.4 EDR A =0.8 Slot T (HC=0, EDR=1)

21 Page: 21 WMNL Distributed Wakeup Scheduling Sink broadcasts a packet that includes its EDR(1), WS(T) and HC(0) Every node except the sink runs the following algorithm if receives a packet from one of the neighbors Calculates the new HC Calculates the new EDR if the change of EDR is higher than a threshold or the HC is changed Calculates the new WS Broadcasts the new values endif Expected Delivery Ratio (EDR) Hop Count (HC) Wakeup Slot (WS) Selection

22 Page: 22 WMNL Sink … Time … 54 slots Slots 45~53 (HC i, EDR i, WS i ) (0, 1, 54) (1, 0.95, ∞) (1, 0.9, ∞)

23 Page: 23 WMNL (1, 0.95, 47) (1, 0.9, 50) Sink … Time … 54 slots Slots 36~44 Slots 45~53 (HC i, EDR i, WS i ) (0, 1, 54) (2, 0.92, ∞) (2, 0.9, ∞) (2, 0.88, ∞) (2, 0.86, ∞) (2, 0.92, 38) (2, 0.9, 39) (2, 0.88, 40) (2, 0.86, 41)

24 Page: 24 WMNL (1, 0.95, 47) (1, 0.9, 50) Sink … Time … 54 slots Slots 27~35 Slots 36~44 Slots 45~53 (HC i, EDR i, WS i ) (0, 1, 54) (2, 0.92, 38) (2, 0.9, 39) (2, 0.88, 40) (2, 0.86, 41) (3, 0.89, ∞) (3, 0.88, ∞) (3, 0.85, ∞) (3, 0.83, ∞) (3, 0.8, ∞) (3, 0.89, 28) (3, 0.88, 29) (3, 0.85, 31) (3, 0.83, 32) (3, 0.8, 33)

25 Page: 25 WMNL (3, 0.89, 28) (3, 0.88, 29) (3, 0.85, 31) (3, 0.83, 32) (3, 0.8, 33) (1, 0.95, 47) (1, 0.9, 50) Sink … Time … 54 slots Slots 0~8 Slots 9~17 Slots 18~26 Slots 27~35 Slots 36~44 Slots 45~53 (HC i, EDR i, WS i ) (0, 1, 54) (2, 0.92, 38) (2, 0.9, 39) (2, 0.88, 40) (2, 0.86, 41) (4, 0.85, 19) (4, 0.83, 20) (4, 0.82, 21) (4, 0.78, 23) (4, 0.76, 24) (5, 0.80, 11) (5, 0.78, 12) (5, 0.76, 13) (5, 0.75, 14) (5, 0.73, 16) (6, 0.75, 2) (6, 0.73, 3) (6, 0.70, 5) (6, 0.68, 6) (6, 0.6, 7)

26 Page: 26 WMNL (3, 0.89, 28) (3, 0.88, 29) (3, 0.85, 31) (3, 0.83, 32) (3, 0.8, 33) (1, 0.95, 47) (1, 0.9, 50) Sink … Time … 54 slots Slots 0~8 Slots 9~17 Slots 18~26 Slots 27~35 Slots 36~44 Slots 45~53 (HC i, EDR i, WS i ) (0, 1, 54) (2, 0.92, 38) (2, 0.9, 39) (2, 0.88, 40) (2, 0.86, 41) (4, 0.85, 19) (4, 0.83, 20) (4, 0.82, 21) (4, 0.78, 23) (4, 0.76, 24) (5, 0.80, 11) (5, 0.78, 12) (5, 0.76, 13) (5, 0.75, 14) (5, 0.73, 16) (6, 0.75, 2) (6, 0.73, 3) (6, 0.70, 5) (6, 0.68, 6) (6, 0.6, 7) 12 2029 39 47 54

27 Page: 27 WMNL Performance Evaluation Introduction and Goals Wakeup Scheduling Algorithm Conclusions

28 Page: 28 WMNL Simulation Parameters SimulatorWSNet Deploy Nodes250 nodes Network Size150m * 150m Slots750, 1000, 2000, 3000 slots Hop Count Bound10 hops Run Time100 ModulationFSK Data Rate19.2 kbps

29 Page: 29 WMNL Performance metrics Delivery Ratio End-to-End Delay Energy Consumption Impact factor Density and Link Quality Duty Cycle Sink Position

30 Page: 30 WMNL Experiments Experiment 1Each node only considers the neighboring nodes with the lower HC Experiment 2 Every node considers the neighboring nodes with not only the lower HC but also the same HC Sink HC=1HC=2HC=3HC=4HC=5HC=6

31 Page: 31 WMNL Comparison WSEDR Random

32 Page: 32 WMNL Delivery Ratio (Duty-Cycle ： 0.1%, Sink Location ： (75,75)) Experiment 1Experiment 2

33 Page: 33 WMNL Delivery Ratio (α ： 0.3, Sink Location ： (75,75)) Experiment 1Experiment 2

34 Page: 34 WMNL Delivery Ratio (Density ： 29 neighbors, α ： 0.3, Duty-Cycle ： 0.1%) Experiment 1Experiment 2

35 Page: 35 WMNL End-to-End Delay (Duty-Cycle ： 0.1%, Sink Location ： (75,75)) Experiment 1Experiment 2

36 Page: 36 WMNL End-to-End Delay (α ： 0.3, Sink Location ： (75,75)) Experiment 1Experiment 2

37 Page: 37 WMNL End-to-End Delay (Density ： 29 neighbors, α ： 0.3, Duty-Cycle ： 0.1%) Experiment 1Experiment 2

38 Page: 38 WMNL Energy Consumption (Duty-Cycle ： 0.1%, Sink Location ： (75,75)) Experiment 1Experiment 2

39 Page: 39 WMNL Energy Consumption (α ： 0.3, Sink Location ： (75,75)) Experiment 1Experiment 2

40 Page: 40 WMNL Energy Consumption (Density ： 29 neighbors, α ： 0.3, Duty-Cycle ： 0.1%) Experiment 1Experiment 2

41 Page: 41 WMNL Performance Evaluation Introduction and Goals Wakeup Scheduling Algorithm Conclusions

42 Page: 42 WMNL Proposes a novel forwarding scheme for ultra-low duty-cycle WSNs. –Improve the energy efficiency –Decrease end-to-end delay –Maximizes the delivery ratio –Distributed scheduling –Highly suitable for ultra-low duty-cycle real-time event-driven WSN

43 Page: 43 WMNL

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