Scalable Routing In Delay Tolerant Networks

1. Scalable Routing In Delay Tolerant Networks Mohammad Reza Faghani

2. Mars Mars Jupiter Mars station Earth An Outer Space Network

3. What is Delay Tolerant Networks ? • Intermittent link (dis)connection • No guarantees on End-to-End path • Frequent long duration partitioning C B A D E F

4. What is Delay Tolerant Networks ? • High latency, low data rate • Order of hours latency • Long queuing times • Because of disconnections (Store and Forward) • Extremely large (hours, even days) • Constraints on end node • Limited power, limited buffer • How packets route !?

5. Routing in DTN • DTN Routing Challenges. • Instantaneous end to end path may not exist. • Large queuing delays. • Buffer limitations at intermediate nodes. • Large messages.

6. Routing in DTN • Routing Goals: • Eventual Delivery (delivery ratio) • Minimizing delivery delay • Scalability • Cost-effective

7. The Routing Problem in DTN • Nodes with finite storage capacity • Links with dynamic behavior • Time varying capacity (c(t)) • C(t) = 0, if link is down • Message • Src, Dst, start-time, size • Output: Compute path(s) for every message • Objective: Minimize delay • Other objectives: message delivery ratio, minimize $$ cost

8. The Routing Problem in DTN • Edge parameterized by • Source • Destination • capacity function • delay function. • Define link costs and find minimum cost path. • Cost varies with time. • Compute minimum cost paths over this dynamic cost assignment • Modified Dijkstra by taking into account time of arrival

9. Input variable used in Routing • Contacts • Complete link time variant datas • Contacts summary : • Time independent information • Average waiting time until the next contact • Queuing : Link queues, available storage • Traffic Demand

10. Routing input vs. Performance LP distributed Contacts + Global Queuing + Traffic Demand EDAQ EDLQ Contacts + Global Queuing “Performance” Contacts + Local Queuing ED MED Contacts Contacts Summary Input variable used

11. Routing in large networks • As the network size grows, number of contacts increases. • These algorithms are not scalable for large networks. • Using the idea used in static scalable routing. • The hierarchical routing

12. Scalable Routing in DTNs • Cong et. al. proposed a simple DTN model. • This makes hierarchical routing possible • For scalability, defined two contact information compression methods.

13. Simplified DTN model 6 • Static nodes (white) • Mobile nodes with repetitive motion • Motion cycle: • T1=2 mins, T3=T4=3 mins • Contact: a time period for communication. • Persistent contacts: (2,1), (3,4), & (5,6) • Persistent contact: (ni nj - - -) • Predicted contacts: (1,3), (3,6), & (4,5) • Predicted contact: (ni nj Tij tstart tduration) 5 3 1 2 4

14. Hierarchical Routing in Static Networks • Hierarchical network • Uses multilevel clustering. • Offers scalable management of routing tables. • Hierarchical routing • Uses the hierarchical network as a topology abstraction • A top-down process: the decision made in a higher level is more important • Clustering & Clusterhead 10 11 15 12 24 2 2 1 1 19 13 22 8 14 6 6 20 21 18 23 4 4 5 5

15. Hierarchical Clustering in Static Networks 2 Level 2 3 1 2 7 3 6 4 5 Level 1 Level 0 10 25 11 12 1 1 1 19 16 15 24 2 2 2 7 7 7 9 22 17 20 21 13 18 8 3 3 3 23 14 6 6 6 4 4 4 5 5 5

16. Hierarchical Clustering in Static Networks 1 2 Level 2 3 1 2 7 3 6 4 5 Level 1 Level 0 10 25 11 12 1 1 19 16 15 24 2 2 7 7 9 22 17 20 21 13 18 8 3 3 23 14 6 6 4 4 5 5

17. Hierarchical Clustering in Static Networks • Before any routing each node in the network needs to obtain the topology information of its clusters in all levels. • Source should know the hierarchy address of destination.

18. Hierarchical Clustering in Static Networks 1 2 Level 2 3 1 2 7 3 6 4 5 Node 61 represents the cluster of nodes 60,80,240 All nodes have their own hierarchy address e.g. node 6 HA equals (13, 22, 61, 80). Level 1 Level 0 10 25 11 12 1 1 19 16 15 24 2 2 7 7 9 22 17 20 21 13 18 8 3 3 23 14 6 6 4 4 5 5 18

19. Hierarchical Routing in Static Networks 1 2 Level 2 3 1 2 7 3 6 4 5 Level 1 Level 0 10 16 11 12 1 1 19 16 15 24 2 2 7 7 9 22 17 20 21 13 18 8 3 3 23 14 6 6 4 4 Destination 5 5 Source 19

20. Hierarchical Routing in DTNs • Hierarchical routing • Similar to that in static networks • Multilevel clustering • Clusterhead selection • Links: contact information aggregation • Contact information compression methods

21. Cluster head Selection • Objective • Clusterhead: the center (in terms of delay) of a cluster • Cluster members are close to their clusterheads • Absolute priority • D(i,j) is the weighed average delay between nodes i and j • Higher if n is closer to the shortest paths among its neighbors • Clusterheads that have the highest APs are self-selected. • Relative priority • Node i selects a nearby clusterhead n who has a high AP

22. Contact information aggregation 6 • Hierarchical links havetime-variant delays • They contain aggregatecontact information • Contact information ina level k+1 link are aggregated from therelated level k links. 5 3 1 2 4

23. Contact information compression • Aggregation level (La) • Above La, each link contain only a constant delay

24. Contact information Compression • Contact information aggregated to link (6,7) is shown in (c). • There are two possible shortest paths across the time as shown in (d) & (e) • The contact information stored by link (6,7) after contact information removal

25. Hierarchical Routing in DTNs • Similar to Hierarchical Routing in static networks • Hop by hop routing • A top-down decision making within each hop • Step 1: top-down routing • When the routing process is above La • Step 2: Routing with contact information • Routes on the combined contact information in all clusters below La

26. Simulation • An examplenetwork • Static nodes • Mobile nodes • Mobile node • Whose trajectorytravels severalrandom waypointswithin a randomsquare bound

27. Simulation Results • Route length Distribution

28. Simulation Results • Hop-countratio • 70/30

29. Simulation Results • Delay ratio • 70/30

30. Simulation Results • DHR+CIRDelay ratio • 70/50

31. Simulation Results • Storage communication overhead

32. Summary • Summary • Routing performance is close to the optimal routing result in terms of hop-count and delay • Routing performance improves as aggregation level (La) increases • Routing performance improves as the source and destination distance increases • Storage and communication overhead is reduced by the compression methods while desirable routing performance and scalability is achieved.

33. References • [1] Liu C,Wu Jie. Scalable Routing in Delay Tolerant Networks.In proc. of the 8th ACM International Symposium on Mobile Ad Hoc Networking and Computing (MobiHoc), 2007 • [2] S. Jain, K.Fall, and R.Patra. Routing in Delay Tolerant networks. In Proc. of ACM SIGCOMM, 2004 • [3] Leonard Kleinrock, Farok Kamoun, "Hierarchical Routing for Large Networks, Performance Evaluation and Optimization", Computer Networks, Vol. 1, No. 3, pp. 155–174, January 1977

34. Questions !?