Routing for Intermittently connected Networks

1. Routing for Intermittently connected Networks Harish Ramamurthy and Advait Dixit

2. Presentation Outline • Introduction • Basic Scenario and Motivation • Goals • Solution Outline • Design Issues and Tradeoffs • Existing Solutions • Epidemic Routing • Probabilistic Routing – PROPHET • Gossip based ad-hoc routing • Conclusion

3. Basic Scenario • Receiver location/route unknown at the sender • Complete communication path may not exist at any time between the communicating endpoints • Utilizing mobility to complete the communication path • Efficiently flood the network (!)

4. Applications • Mobile Sensor Networks • ZebraNET • Shared Wireless Info-station Model • Military and Disaster Recovery • Conveying environmental Hazards • Satellite and Interplanetary Communications • Communication in rural villages • Postman model

5. How is this different from … ? • Delay Tolerant Networking (DTN) • More inclined towards addressing joining “disjoint networks” issues • Routing is a small component of the entire framework • Ad-hoc routing • Complete communication path may not exist at any time

6. Solution Mechanism Outline • Store and Forward • Utilize Mobility Source: Lindgren et al []

7. Goals • Maximize Delivery Rate • Minimize Resource Consumption • Bandwidth/Energy • Storage • Computation • Minimize Latency • Time taken for the message to get delivered • Security Considerations

8. Design Issues and Tradeoffs • Forwarding Decision • Fixed (Epidemic Routing) • Probabilistic • Learning from scenario ( Gossip based ad-hoc routing) • Learning via history (PROPHET) • Cache Maintenance • Queuing • FIFO • WFQ • Buffer Preference • Reliability • Acknowledgements (Deletion Vectors!) • Security

9. Epidemic Routing – Vahdat, Becker et al. • Forwarding Decision • Fixed – Flood the entire network! • Cache Maintenance • Queuing • FIFO • Buffer Preference • Reliability • Acknowledgements • Security • Assumption • Nodes are randomly mobile • Nodes have sufficient resources – Energy, Buffer Size etc.

10. Epidemic Routing Protocol • Definition of Terms • SV  Summary Vector • Protocol Flow • Node with smaller identifier initiates an “anti-entropy” Session • Cache Maintenance • FIFO Queuing per-host • New messages given preference over old ones in terms of buffer availability Source: Vahdat, Becker et al.

11. Implementation Monarch [2] – Extends ns-2 simulator for wireless and mobile protocols Epidemic Routing Protocol over Internet MANET Encapsulation Protocol (IMEP) Simulation Scenario 50 nodes randomly placed in 1500m x 300m grid Nodes randomly mobile with average speed 10 m/s (Range 0 – 20 m/s) Implementation and Simulation Scenario

12. Simulation Results

13. PROPHET – Lindgren, Doria et al. • PROPHET stands for Probabilistic Routing Protocol using History of Encounters and Transitivity • Observation: Real users move in a predictable fashion rather than randomly • Forwarding decision is based on a probabilistic metric called delivery predictability (P(a,b)) that is set up at every node a for each known destination b.

14. Delivery Predictability Calculation • Updated every time a node is encountered • Aged after every time unit (γ is the aging constant.) • Impact of transitive property on deliver predictability

15. Message Forwarding Strategies • Message is transferred if the delivery predictability of the destination of the message is higher at other node. • Other strategies • Select a fixed threshold.

16. Simulation Scenario • 50 nodes placed randomly in 1500m * 300m area • Divided area into 12 sub areas • Mobility Model

17. Simulation Results Delivery rates

18. Simulation Results (contd.) Average delay

19. Simulation Results (contd.) Number of forwarded messages

20. Gossip-Based Ad Hoc Routing Advait Dixit

21. Motivation • Ad-hoc network routing protocols like AODV, DSR, TORA flood routing messages in the network • Many of these routing messages need not be transmitted • The Gossip-based approach: Each node forwards a message with some probability.

22. Basic Gossiping Protocol - GOSSIP1(p) • Source sends route request with probability 1 • When a node receives route request, it broadcasts the request with probability p • If the node receives the same request again, it discards it

23. Modified Gossip – GOSSIP1(p,k) • Observation: Gossip may die quickly if source has few neighbors • To overcome this problem, gossip with probability 1 for the first k hops before continuing gossip with probability p

24. Observation: Bimodal Behavior • In all the executions, either hardly any nodes receive the message or most of them do

25. Some Experimental Results • Increase in degree of the network increases probability of receiving message • Boundary effect: Nodes on the boundary have lesser probability of receiving the message.

26. Heuristics – GOSSIP2(p1, k, p2, n) • Assumption: Node has accurate information regarding its neighbors • Protocol has 4 parameters: p1, k, p2, n • p1 and k are same as GOSSIP1(p, k) • Neighbors of nodes with fewer than n neighbors gossip with probability p2

27. Some More Heuristics • Preventing premature gossip death – GOSSIP3(p, k, m) • If a node has n neighbors, it should get p*n messages from its neighbors • If it receives significantly lesser messages, it indicates gossip is dying • Retries • Assumption: Networks are well connected • No acknowledgements indicate gossip death • Bimodal behavior becomes an advantage • Disadvantage: Increased latency

28. Implementation and Simulation Scenario • Implementation with AODV • Use GOSSIP3(0.65, 1, 1) rather than flooding the network. • Timeout period was 5 * NODE_TRAVERSAL_TIME. • Simulation Scenario • 150 nodes • Grid of 3300m * 600m • 30 connections generating 2 packets/sec • Random way-point mobility model

29. Simulation Results Normalized routing load Packet Delivery Fraction

30. Simulation Results (contd.) Average delay:

31. Conclusion • Key Issues • Forwarding Decision • Cache Maintenance • Reliability • Essentially  Techniques of efficiently flooding the network!

32. References • A. Vahdat and D. Becker, "Epidemic Routing for Partially-connected Ad Hoc Networks,“, Technical Report CS-200006, Duke University, April 2000 • MONARCH Wireless and Mobility Extensions to ns-2: http://www.monarch.cs.rice.edu/cmu-ns.html • Alan Demers, Dan Greene, Carl Hauser, Wes Irish and John Larson, “Epidemic algorithms for replicated database maintenance”, Proceedings of the ACM Symposium on Principles of distributed computing • A. Lindgren, A. Doria, and O. Schelén, “Probabilistic Routing in Intermittently Connected Networks,” in Proceedings of the Fourth ACM International Symposium on Mobile Ad Hoc Networking and Computing (MobiHoc 2003) • Zygmunt Haas, Joseph Y. Halpern, Li Li, “Gossip-Based Ad Hoc Routing,” IEEE Infocom 2002 • MANET Chapter: http://www.ietf.org/html.charters/manet-charter.html • AODV homepage: http://moment.cs.ucsb.edu/AODV/aodv.html

33. Thank You!Questions???