1. A Small World Model for Improving Robustness of Heterogeneous Networks Diansong Luo, Tie Qiu*, Nakema Deonauth, Aoyang Zhao Presenter: Tie Qiu (PhD, Associate Professor) School of Software, Dalian University of Technology qiutie@ieee.org Dec. 15, 2015 GlobalSIP 2015

2.  Background and Motivation  Greedy Model with Small World  Simulation Results  Conclusion Outline

3. Background and Movivation (1) Homogeneous network and Heterogeneous network

4.  Constructing an efficient and robust network topology for heterogeneous sensor networks.  Efficiency: high throughput and low latency.  Robustness: acceptable quality of se­r­vice in the presence of faults. Background and Movivation (2)

5.  small world properties  Small world model has desired characteristics for wireless network such as small average path length and high clustering coefficient.  Small average path: only a small number of hops are required to transfer data between any two nodes. This can reduce the time of forwarding.  A high clustering coefficient leads to a greater spread of messages throughout the network. Background and Movivation (3)

6.  How to construct a small-world model in heterogeneous sensor networks?  Introduce a small number of long-range links. Background and Movivation (4)

7. (1) base station (2) wired shortcuts (3) super nodes (4) super nodes (DASM)

8.  Idea ： a)The direction of added-shortcuts should be directed to sink node. b)Different nodes have different importance. Consider the importance of network nodes and add shortcuts between nodes with higher important degree.  We try to ： a)Put forward two greedy criteria. b)Give the concept of local importance of node. c)design the shortcut-added strategy. Greedy Model with Small World(1)

9.  Greedy criteria ： a)The closer to the sink, the better. b)The closer to the straight line that passes by main node and the sink node, the better. Greedy Model with Small World(2) (a) Minimum hop route.(b) The shortest path length route.

10. Greedy Model with Small World(3)

11. Greedy Model with Small World(4)

12. Greedy Model with Small World(5)

13. Greedy Model with Small World(6)

14. Greedy Model with Small World(7)

15. Step 1.

18. Step 2. 1 2 4 3 1 2 3 4 6 5 1 2 3 4 5 6

20. Step 3. 2 2 4 3 3 3 4 4 4 3 3 3 3 5 4 3 3

22. Step 4.

23. Step 5.

26.  Small World Properties Evaluation 500 nodes (RSNs and SSNs) are randomly deployed in a sensor field of 1000*1000m. communication radius of RSNs and SSNs are100 m and 300 m, respectively. Simulation Results(1)

27. monitoring area 1000 * 1000 m 2 Simulation Results(2)

28. Simulation Results(3)

29. Simulation Results(4)  Why do we compare to DASM? GMSW is similar to DASM because the result of two greedy criteria also makes added-shortcut direct to the sink node. The difference is that GMSW emphasizes on the different importance of network nodes when it comes to adding shortcuts, while DASM only pays attention to the direction of shortcuts.

30. Simulation Results(5)

31.  Robustness Evaluation  Experimental environment. Simulation Results(6)

32. Simulation Results(7) monitoring area 1000 * 1000 m 2

33. Simulation Results(8)

34. Simulation Results(9)

35. Conclusion

36. Thanks