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Landmark-Based Information Storage and Retrieval in Sensor Networks Qing Fang Department of Electrical Engineering, Stanford University Jie Gao Department.

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Presentation on theme: "Landmark-Based Information Storage and Retrieval in Sensor Networks Qing Fang Department of Electrical Engineering, Stanford University Jie Gao Department."— Presentation transcript:

1 Landmark-Based Information Storage and Retrieval in Sensor Networks Qing Fang Department of Electrical Engineering, Stanford University Jie Gao Department of Computer Science, Stony Brook University Leonidas J. Guibas Department of Computer Science, Stanford University INFOCOM 2006

2 Outline Introduction Related Work Landmark-Based Data Centric Simulation Conclusion

3 Background sink

4 Background sink

5 Background sink

6 Geographical Hash Table (GHT) lion

7 Disadvantage of GHT No distance-sensitive producer lion consumer

8 Disadvantage of GHT No distance-sensitive Communication bottleneck

9 Disadvantage of GHT No distance-sensitive Communication bottleneck Bad for queries the cross-type data

10 GHT with Structured Replication quad-tree d = 1 4 1 = 4 d = 2 4 2 = 16

11 GHT with Structured Replication d = 1

12 Related Work Title – GLIDER: Gradient Landmark-Based Distributed Routing for Sensor Networks Author – Qing Fang, Jie Gao, Leonidas J. Guibas, Vin de Silva From – INFOCOM 2005

13 GLIDER a b c t s d

14 Overview producer h consumer T1T1 T2T2 T3T3 T4T4 replication path retrieval path

15 Replication Path producer h LaLa LcLc LdLd a LeLe LfLf b LgLg c consumer No distance-sensitive LbLb

16 Distance-sensitive

17 Optimal Principle a → b → c → d → e → f → g c → d → e → f → g

18 Optimal Principle producer h LaLa LcLc LeLe LfLf LgLg consumer LbLb LdLd

19 Finger Tree producer h LaLa LcLc LeLe LfLf LgLg consumer LbLb LdLd

20 Finger Tree LaLa LcLc LeLe LfLf LgLg LbLb LdLd s

21 Replication Path producer h LaLa LbLb LcLc LeLe LfLf LgLg a consumer LdLd

22 Replication Path producer 1 h LaLa LbLb LcLc LeLe LfLf LgLg a producer 2 LdLd

23 Simulation Network Enviroments – 316m × 316m sensing field – 2000 nodes – 11m communication range – 6.2 degrees – 23 landmarks – Simulated with C++

24 Simulation Data structure and storage requirement – The landmarks – Neighborhood distances to its reference landmarks – The hash function – A bit to record it’s on boundary or not – The IDs of its neighboring sensors

25 Simulation Compare producer cost with GHT

26 Simulation Compare consumer cost with GHT

27 Simulation Retrieval Path Length GHT100% Landmark-based70.2%

28 Simulation Load distribution of landmark-based Load distribution of GHT

29 Conclusion A location-free, landmark-based information brokerage scheme for sensor networks – Distance-sensitive – Load-balanced

30 Thank You !


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