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Po-Yu Chen, Zan-Feng Kao, Wen-Tsuen Chen, Chi-Han Lin Department of Computer Science National Tsing Hua University IEEE ICPP 2011 A Distributed Flow-Based.

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Presentation on theme: "Po-Yu Chen, Zan-Feng Kao, Wen-Tsuen Chen, Chi-Han Lin Department of Computer Science National Tsing Hua University IEEE ICPP 2011 A Distributed Flow-Based."— Presentation transcript:

1 Po-Yu Chen, Zan-Feng Kao, Wen-Tsuen Chen, Chi-Han Lin Department of Computer Science National Tsing Hua University IEEE ICPP 2011 A Distributed Flow-Based Guiding Protocol in Wireless Sensor Networks

2 Outline Introduction Goal The proposed guiding protocol Simulation Conclusion

3 Introduction Guiding navigation is one of the major applications in WSNs. Destination Static sensor Moving object

4 Introduction Congestion problem will postpone the escape time Destination Static sensor Moving object A Congestion point

5 Goals We propose a flow-based guiding protocol Consider road capacity and exit capacity Less congested paths to minimize The escape time The congestion time

6 Assumptions and Environment Definitions An indoor 2D environment Several exits and road sections Each sensor knows the distances to each exit Each road section is equipped with one sensor and indicator Responsible for sensing dangerous events Detecting the number of moving objects

7 Assumptions and Environment Definitions Each sensor holds an artificial potential value The indicator is used for showing the guiding information

8 Flow-Based Guiding Protocol Obstacle Sensor 2 Sensor 5 Sensor 7 Sensor 3 Sensor 8 Sensor 6 Sensor 11 Sensor 14 Sensor 10 Sensor 13 Sensor 4 Sensor 9 Exit 1 Sensor 1 Exit 2 Sensor 12

9 Flow-Based Guiding Protocol Our proposed protocol has three phases Initialization phase Computation phase Maintenance phase

10 Flow-Based Guiding Protocol Initialization phase Initialize the potential value of each sensor No people and emergency event Each exit sensor on an exit has a constant maximal potential value It starts broadcasting an initial packet A maximum moving speed of an object The distance from sensor i to an exit e The exit capacity (How many people can pass it)

11 Flow-Based Guiding Protocol Initialization phase

12 Flow-Based Guiding Protocol Computation phase The flow velocity of each road changes d =The number of people/square meters

13 Flow-Based Guiding Protocol Maintenance phase Sensing dangerous events  potential value = 0 The dangerous area will spread among adjacent roads If the objects are too close to the dangerous area, they probably enter the dangerous area The average of all of neighbor potential value A system constant and 0< φ <1

14 Flow-Based Guiding Protocol If φ is high, the escaping paths will be further away from dangerous areas. If φ is low, the escaping paths go along the side of dangerous areas.

15 Flow-Based Guiding Protocol The local maximum problem Objects enters the local maximum road Ping-pong effect Decreasing its potential value to evacuate moving objects The standard deviation of ptl neighbors

16 Simulation Area40.5m x 40.5m Directions6 Each road5m and 1.5m Parameters φ and α Both set to 0.5 V free 1.4 m /s Maximum potential value140 Minimum potential value0 2 4 4 2 2 2

17 Related work : 10 : 11 A:5A:5 :5:5 :8:8 :3:3 :6:6 :5:5 This paper didn’t consider The events flow velocity The difference capacity of each exit

18 Simulation Average escape time

19 Simulation Average congested time

20 Simulation Average moving speed

21 Conclusion We propose a flow-based guiding protocol Guide moving objects to exits safely and quickly Decrease the escaping time and congestion time Balance the traffic load on paths and exits

22 Thank You


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