1. Augmenting the Backpressure Collection Protocol to Support Multiple Sinks Varun Shimoga Prakash, Dr. Omprakash Gnawali Networked Systems Laboratory Dept. of Computer Science University of Houston

2. Problem Statement Enable the Backpressure Routing technique to route packets to multiple sinks within a network.

3. Expectations from the Solution Small Memory Overhead Packet Delivery Performance Adherence to conditions imposed by Backpressure Routing.

4. Possible Solutions Virtualization of Queue Management Clustering of Network Feedback based model.

5. Virtualization of Queue Management Each node stores its local backpressure to each of the sink in the network. Single Queue of Packets Backpressure values create a virtual queue for each sink. Backpressure values propagated through beacons or snooping.

6. Source Node 3 Source Node 4 Source Node 1 Source Node 2 Sink Node 1 Sink Node 3 Sink Node 2

7. { Sink_1: Active } 1 4 3 2

8. { Sink_2: Active } 1 3 2 4

9. { Sink_1: 1 Sink_2: 1 } 4 3 2

10. { Sink_3: Active } 1 2 3 4

11. { Sink_3: 1 } 1 2 3

12. { Sink_3: 2 Sink_1: 2 Sink_2: 2 } 1 2 3

13. { Sink_3: 2 Sink_1: 3 Sink_2: 3 } 1 2 3

14. Disadvantages More the number of sinks, larger the packet header and storage of local backpressure to sinks.

15. Possible Solutions Virtualization of Queue Management Clustering of Network Feedback based model.

16. Clustering of Network Create imaginary clusters in the network where sinks are the centroids. Controlled Broadcast until packets reach a node in the desired cluster of a sink.

17. The Network is clustered around each Sink. There is an affiliation of each of the Nodes towards the cluster to which it belongs.

18. Source Sink

19. Broadcast Message

21. This node has a gradient sloping towards the local sink. Route message through Backpressure routing.

22. Disadvantages Controlled Broadcasting does not allow Linear Networks. Without controlled broadcasting, undesirable redundancy of messages increases.

23. Possible Solutions Virtualization of Queue Management Clustering of Network Feedback based model.

24. Feedback Based Model Sink sends feedback to the last node before it. Feedback propagate to all nodes in network. Based on feedback and past performance, nodes choose their next hop.

25. Source Node 3 Source Node 4 Source Node 1 Source Node 2 Sink Node 1 Sink Node 3 Sink Node 2 Task: Send packets from Source Node 3 to Sink Node 1

26. 1 2 3 Initially Broadcast the packet

27. 1 2 3 Broadcast

28. 1 2 3 Negative Feedback

29. 1 2 3 Broadcast Negative Feedback Sink Node 1 Positive Feedback

30. 1 2 3 Sink Node 1 Positive Feedback Sink 1:

31. 1 2 3 Sink Node 1 Positive Feedback Sink 1:

32. 1 2 3 Sink Node 1 Positive Feedback Sink 1: Sink 2: Sink Node 2 Sink 3:

33. Disadvantages Convergence of the entire network takes more time in case of mobile sinks. New weight parameter (feedback) to be considered to calculate weight.