1. A Spatial-based Multi-resolution Data Dissemination Scheme for Wireless Sensor Networks Jian Chen, Udo Pooch Department of Computer Science Texas A&M University Yong Guan Department of Electrical & Computer Engineering, Iowa State University IEEE IPDPS 2005 Speaker ： Shih-Yun Hsu

2. Outline  Introduction  Assumption  Spatial-based Multi-resolution Data Dissemination (SMRDD)  Performance Evaluation  Conclusions

3. Introduction  Energy efficient data-gathering techniques are important  Data gathering techniques are divided into three categories:  Local-storage  External-storage  In-network data-centric storage

4. Introduction  Local-storage and external-storage  Sinks have to keep broadcasting queries to maintain paths for data retrieval from data sources  Directed Diffusion (DD)  In-network data-centric storage  When a large volume of data needs to be transmitted for storage elsewhere, it’s not a good choice

5. Introduction  Motivation  Local-storage  Energy efficiency  Reducing dissemination of redundant data

6. Assumption  A large scale sensor network  Each sensor node  Static  Energy-constrained  Uniform transmission range  Knows its location (GPS or other mechanisms)  High density

7. Spatial-based Multi-resolution Data Dissemination (SMRDD)  Definition of Resolution Levels  Querying Scheme  Query and Data Forwarding  On-demand GPSR

8. Definition of Resolution Levels Low resolution Medium resolution High resolution

9. Definition of Resolution Levels d a The highest resolution level Pixel point

10. Definition of Resolution Levels

11. g1 n1 n3 n4 n2

12. Definition of Resolution Levels g1 n1 n2 n3 n4

13. Querying Scheme  Data-independent Querying Scheme  Data-associated Querying Scheme

14. Data-independent Querying Scheme

16. Data-associated Querying Scheme Sink

17. Data-associated Querying Scheme

18. Query and Data Forwarding  G=(V, E)  V={all pixel nodes and sink}  E= the set of interconnections among pixel points and the sink  T is a a subset of E that connects all of nodes  The weight (the distance between two nodes) is minimum

19. On-demand GPSR  Identifying Destination with Location Instead of Node Identifiers  State Transformation of Nodes in OD-GPSR

20. Identifying Destination with Location Instead of Node Identifiers Beacon Data Location Infomation

21. Identifying Destination with Location Instead of Node Identifiers Radio range ≦ 1/2 radio range Location

22. State Transformation of Nodes in OD-GPSR A node without neighbor information A node with neighbor information A node will collect neighbor information

23. Performance Evaluation  Using ns-2 simulator  Randomly distributed in a 256×256 m 2 field  Radio range is 40 m

24. Performance Evaluation

27. Conclusions  The resolution is application-based, depending on sensors’ sensing range for tasks  In addition to avoiding query flooding and extra cost for data-centric storage, other method elicits less redundant data and achieves further energy efficiency  The data-associated querying scheme renders the data retrieved each time with more fidelity

28. Thank You