Longjiang Guo Heilongjiang University longjiangguo@gmail

1. EBAS: An Energy-Efficient Event Boundary Approximated Suppression Algorithm in Wireless Sensor Networks Longjiang Guo Heilongjiang University longjiangguo@gmail.com

2. Outline • Introduction • EBAS Algorithm • Experiment And Result Analysis • Conclusion

3. Introduction • Event Boundary Approximated

4. Example • Forest fire alarm system

5. Challenge • Sink has to collect information from all the nodes that lie in field boundaries. • Therefore: • A lot of the number of sending messages • Much more energy consuming • The higher the message packets collision rate

6. Resolving  • Based on the above challenge, we propose a novel energy-efficient algorithm (EBAS). • In EBAS, sink do not need all the information from the nodes in field boundaries. • EBAS supports a suppression scheme that conservers energy by reducing the number of sending message.

7. Outline • Introduction • EBAS Algorithm • Experiment And Result Analysis • Conclusion

8. EBAS algorithm • EBAS is composed of three parts • Key node automatically selection in-network • Transportation • Event boundary rebuilt

9. Key node selection • Definition 1 :[Slope] We define the slope of a sensor node i which lies in an event boundary as following: Given the coordination of sensor node i as (Xi, Yi) and the coordination of the neighbor j of sensor node i as (Xj, Yj), we calculate the slope of sensor node i with its neighbor j as following:

10. Key node selection • Definition 2. [Verge Node] A node is called verge node if it has only one neighbor on an event boundary. • Definition 3. [Key Node] A sensor node m is called Key node if and only if it satisfies one of the following 2 conditions: (1) Difference of slopes with its two neighbor nodes i and j outrages the predefined threshold, ε. i.e. (2) It is a verge node in an event boundary.

11. Slope: K23, 24=-2, K23, 22=0.5. Node 1 and node 27 is Verge Node. When ε=0.5 , | K23, 24 -K23, 22|>0.5 ,so node 23 is a Key Node

12. Key node selection • Initialization Phase: • Individual behavior :Each node lies in an event boundary broadcasts its node ID and coordination (ID, X, Y) to its neighbors. • If a node just gets one message. Definition 2 • If a node just gets two messages. Definition 3 • if a node receives more than 2 messages, for each received node id, calculate the distance between the two nodes using Euclidean distance, then sort these distances, pick out the 2 nodes with least distances. Then apply Definition 3.

13. EBAS algorithm • EBAS is composed of three parts • Key node automatically selection in-network • Transportation • Event boundary rebuilt

14. Transportation • Building aggregation tree • Transportation key node information • Suppression Strategy

15. Building aggregation tree • There are two types of message package in building aggregation tree: one is Tree-building package: • (PackageType=1, NodeID, level) • (PackageType=2, ParentNode, NodeID). • Initialization sink node broadcasts the Tree-building package (1, sink’s NodeID, 0) and set the local level with 0. • Individual Behavior Each node in senor networks maintains three variables: parent, child and level which are initialized with null, null, and . parent, child and level indicate the parent, children and level of sensor node in aggregation tree respectively.

16. Example

17. Transportation key node information • Given a set of key nodes Mi={di1, di2, di3, …} located on sensor node i. Sensor node i will send Mi to his parent node. Suppose j is a parent node in aggregation tree. i1, i2 …ik are j’s children. When sensor node j receives Mi1, Mi2 …Mik, sensor node j will unite Mi1, Mi2 …Mik as following operation: (1) MjMi1Mi2 …Mik.. (2) Sensor node j sends Mj to his parent.

18. Suppression Strategy • Given a set of key nodes M= {di1, di2, di3 …}, the FM sketch of M, denoted S (M), is a bitmap of length k. The entries of S (M), denoted S (M) [0… k-1], are initialized to zero and are set to one using a random binary hash function h applied to the elements of M. Formally,

19. EBAS algorithm • EBAS is composed of three parts • Key node automatically selection in-network • Transportation • Event boundary rebuilt

20. Event Boundary Rebuilt • Transportation over,Since we know exactly all key node ID, we can put event boundary rebuilt easy.

21. Outline • Introduction • EBAS Algorithm • Experiment And Result Analysis • Conclusion

22. Experiment and result analysis • We have completed EBAS implementation in the TinyOS2.x TOSSIM simulator. • The accuracy error is defined as follows: This Figure shows that the accuracy of EBAS mainly depends on the predefined threshold, ε. The smaller the predefined threshold is, the smaller the accuracy error of the recovered event boundaries is.

23. Message quantity with slope threshold varying

24. Outline • Introduction • EBAS Algorithm • Experiment And Result Analysis • Conclusion

25. Conclusion • In this paper, we present a novel energy-efficient algorithm EBAS to solve event boundaries transportation problems. • The entire idea can be divided into 4 parts: • Key node generation; • Key nodes set suppression; • Transportation; • Decompression. • Our experiment results confirmed the correctness and effectiveness of our algorithm.

26. Thanks