1. Song Wei Enabling Distributed Throughput Maximization in Wireless Mesh Networks A Partitioning Approach

2. Problem ● Channel Scheduling  Centralized  Distributed

3. Model ● Graph theory  Conflict graph  Graph coloring ● Throughput Constrains ● Arrival Process ● Stable Region

4. A Simple Example 1 2 3 4 56 1 2 3 4 56

5. ● Conflict Graph

6. A Simple Example ● Stability Region For single radio, b=1. For two radios, b=2. Etc :Arrival process on link (i, j) lambda: arrival rate Stability Region:

7. A Simple Example ● Scheduling  Centralized: Yes  Distributed: ?

8. A Simple Example ● Partition: 100% Distributed Scheduling 1,2 2,3 3,4 4,5 5,6 6.1 1,2 2,3 3,4 4,5 5,6 6.1

9. A Simple Example ● Capability Increase 1 2 3 4 5 6 1 2 3 4 5 6 1 2 3 4 5 6

10. A Simple Example ● Insight  Topology study  Divide and conquer  Better the dividing

11. Topology for 100% DS ● Local Pooling

12. Topology for 100% DS ● Local Pooling Building Blocks  1-5  6  7

13. Topology for 100% DS ● Construction of Local Pooling network  Clique  Clique Connection  Tree of Cliques  Segments connected Cliques  Tree of Blocks

14. Topology for 100% DS ● Tree

15. Partition ● Problem  Multi Radio – Multi Channel Model  Formulation

16. Partition ● Algorithm  BFS : O(k(m+n))  MCI :

17. Improve Capacity

18. ● How to define Capacity here?  Average  Max ● What’s the bottle neck?  Degrees of vertexes in first partitions are too high ● How to solve it?  Balance degree of vertex

19. Improve Capacity ● R-Greedy

20. Improve Capacity ● R-MaxD  Alter path  Consider Max Degree Vertex

21. Improve Capacity ● R-AvgD  Alter path  Consider All Vertex with no TF degradation

22. Performance Evaluation ● Partitioning

23. Performance Evaluation ● Capability Expansion

24. Questions ● Thanks