1. LPT for Data Aggregation in Wireless Sensor Networks Marc Lee and Vincent W.S. Wong Department of Electrical and Computer Engineering, University of British Columbia, Canada Globecom 2005

2. Outline Introduction The Lifetime-Preserving Tree (LPT) Construction Algorithm Centralized Approach Distributed Approach Simulation Conclusions

3. Introduction --- background Since sensors are densely-deployed in WSNs Detection of event can trigger the response from many nearby sensor nodes (sources) Sources would aggregate the data locally to remove any redundancy

4. Introduction --- background By choosing the Directed Diffusion as the underlying routing platform Sink Source

5. Introduction --- problem formulation By balancing the lifetime of each source The frequency of tree reconstruction can be reduced E-Span

6. Introduction --- motivation and goal Motivation Consider residual energy of sources in tree construction Goal Prolong the lifetime of the sources which are transmitting data reports periodically

7. LPT --- Centralized Approach Tree energy: directly depend on the minimum energy of any non-leaf node Identify this minimum energy node (which represents the bottleneck to the network) bottleneck

8. LPT --- Centralized Approach Arrange nodes in ascending energy levels Start from the node with the least energy Test whether the removal of all the network links to this node except from its highest-energy neighbor will disconnect the existing graph

9. LPT --- Distributed Approach Explore the Highest-Energy Branch from every source to any Root Each source node to initiate a message in a format that contains its energy information

10. LPT --- Distributed Approach Branch energy=8 Branch energy=6 According to the received branches Identify tree energy Each source broadcasts its tree structure and selects the one with the highest tree energy

11. LPT --- Distributed Approach Preserve the loop-free property of the tree Branch energy=7

12. Simulation Simulator : ns-2 Sensor node : range from 50 to 250 increment of 50 Randomly deployed in the field Average node density : 50/160 nodes/m 2 Sources is 10% sensor nodes 5 sinks

13. Simulation Percentage difference on tree energy between distributed and centralized LPTs

14. Simulation average dissipated energy: the average amount of energy consumed by a relaying sensor node

15. Simulation Average node lifetime for each source with M = 250 nodes

16. Simulation The Directed Diffusion has its network overloaded with data traffic when more sources are sending packets

17. Conclusions Proposed an Lifetime-Preserving Tree (LPT) the sources within the event region form a tree to facilitate data aggregation The average node lifetime for source using LPT higher than that of the Directed Diffusion and E-Span