A Probabilistic Routing Protocol for Mobile Ad Hoc Networks

1. A Probabilistic Routing Protocol for Mobile Ad Hoc Networks Abdallah Jabbour • James Psota • Alexey Radul {ajabbour, psota, axch}@mit.edu 6.829 Final Project

2. presentation notes (delete this slide) • slides are currently not formatted; formatting will occur after content is more finalized; please don’t worry about that for now • total presentation time: ~15 minutes (5 min questions)  10-15 slides total • should give protocol a name! • need to add figures, but will talk to teammates first • may need to consolidate/merge slides… • I’d like to add an animation/diagram of the protocol in action 6.829 Final Project

3. Routing in Ad Hoc Networks • Most routing protocols… • Use fixed route to send all packets from a given source to a given destination • Send along path with minimum hop count • Use two main types of packets • Data packets • Control (routing) packets • <one reason why these are bad> • We think we can do better! 6.829 Final Project

4. Outline • Related Routing Protocols • DSDV, DSR, AODV • Probabilistic Routing Protocols • Shortcomings of Related Protocols • Protocol Description • Simulation Overview and Results • Conclusion 6.829 Final Project

5. Related Routing Protocols • Destination-Sequenced Distance Vector • Loop-free, hop-by-hop distance vector • Routes prioritized by sequence numbers • Dynamic Source Routing • Employs source routing • Floods route requests • Maintains routes by link breakage notification • Ad Hoc On-Demand Distance Vector • Combines sequence numbers from DSDV and Route Discovery from DSR 6.829 Final Project

6. Probabilistic Routing Protocols • Control and routing information (“ants”) sent randomly • Data forwarded deterministically to path with best metric • Examples • Ant-Based Control (ABC) • AntNet • Ant-Colony-Based Routing Algorithm (ARA) 6.829 Final Project

7. Drawbacks and Limitations of Above Protocols • Routing packets hinder performance • Decreases available bandwidth • Increases transmission latency • High recovery latency due to static routes • DSDV, DSR, AODV • Probabilistic protocols incorrectly assume symmetric traffic • Above protocols use shortest hop routes • Tends to choose routes with less capacity than optimal ones • Tends to use marginal links 6.829 Final Project

8. Our Protocol’s Design Goals • Minimize routing packets • Especially those interfering with traffic • Use a better measure of network state than minimum hop count to make forwarding decisions • Better cope with link outages 6.829 Final Project

9. Protocol Overview • Minimize control packets by prepending protocol-level headers onto all data packets • Both when originating and forwarding a packet • Nodes promiscuously listen to all traffic, using protocol headers to update state • Base routing decisions on link loss ratios • Modular in both choice of metric and metric to probability mapping • Use ETX instead of minimum hop count 6.829 Final Project

10. Random Routing • Nodes forward probabilistically to neighbor ni with probability pi n1 routingtable p1 = 0.1 s n2 d p1 = 0.4 p3 = 0.5 n3 • Route is not fixed, so packets can still reach destination immediately upon link breakage 6.829 Final Project

11. Random Routing • Nodes forward probabilistically to neighbor ni with probability pi n1 routingtable p1 = 0.3 x s n2 d x x x p1 = 0.4 link breaks! p3 = 0.7 n3 • Update forwarding probability upon link breakage (nodes see infinite loss ratio on link) 6.829 Final Project

12. Deterministic Routing • Forward ALL packets along path with best metric • Our flexible infrastructure allowed simulation of both • First to compare Random to Deterministic Routing 6.829 Final Project

13. Node State • Nodes maintain the following state • Dynamically-updated set of neighbors • Loss ratios to and from each neighbor • Routing state • Metric values for each destination and each neighbor-destination pair • Probability of forwarding to a certain neighbor in order to reach a desired destination • Requests and fulfillments thereof for information about destinations 6.829 Final Project

14. Protocol Header Contents • Each outgoing packet contains a protocol-level header 6.829 Final Project

15. State Update • Nodes update state • Upon sending • Upon receiving • Periodically • Refresh stale state and alert neighbors that you’re still alive • Probability Distribution Updates • Probability distribution and metric values updated along with other node state • Values evolve in response to nodes entering and leaving the system and changes in link quality 6.829 Final Project

16. Simulation Environment • 50 mobile nodes in 1500m x 300m area • Random waypoint movement model • 900s simulation time • We investigated… • Pause times • Node speeds • Connection patterns • Packet sizes • Used 30 CBR UDP sources • Avoid TCP because YYY 6.829 Final Project

17. Evaluation Measures • Packet delivery ratio • Packet delivery latency • Goodput • Number of bytes of overhead • Path length optimality • Transmission overhead • Route acquisition latency 6.829 Final Project

18. Simulation Results 6.829 Final Project

19. Conclusions 6.829 Final Project

20. insert title slide 6.829 Final Project

21. Backup Slides 6.829 Final Project

22. Implementation Overview • ns-2 with Monarch mobility extensions used to model mobile ad hoc network • Implemented protocol in C++ • Data generated by 30 CBR UDP sources • Metrics 6.829 Final Project

23. Routing and Distribution Updates • Random Routing • Each node sends probabilistically to neighbor i with probability pi for destination d • Deterministic Routing • Each node sends exclusively to neighbor i when probability pi for destination d is highest • Our flexible infrastructure allowed simulation of both 6.829 Final Project