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. 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 • Can we do better? 6.829 Final Project

3. Outline • Related Routing Protocols • DSDV, DSR, AODV • Probabilistic routing protocols • Shortcomings of related protocols • Protocol description • Simulation environment • Measures of evaluation • Simulation results • Conclusions and future work 6.829 Final Project

4. Related Routing Protocols • Destination-Sequenced Distance Vector (DSDV) • Hop-by-hop distance vector protocol • Routes tagged with sequence numbers • Proactive • Dynamic Source Routing (DSR) • On-demand source routing • Floods route requests • Maintains routes by link breakage notification • Ad Hoc On-Demand Distance Vector (AODV) • Borrows sequence numbers from DSDV and the Route Discovery mechanism from DSR • Uses RREQ, RREP, RREP ACK, RERR and HELLO packets 6.829 Final Project

5. Probabilistic Routing Protocols • Routing table entries have probability values corresponding to each destination-neighbor pair • Control packets (“ants”) sent randomly • Data forwarded deterministically along path with best metric (number of hops) • Examples • Ant-Based Control (ABC) • AntNet • Ant-Colony-Based Routing Algorithm (ARA) 6.829 Final Project

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

7. Questions That Need Answers • Is it possible to minimize routing packets? • Especially those interfering with data traffic • How can nodes cooperate with little or no control traffic? • Can nodes make forwarding decisions based on a better measure of network state? • How can nodes better cope with link outages? • Which is better: random routing or deterministic routing? 6.829 Final Project

8. Our Answers… 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 cooperate by promiscuously listening to all traffic, using protocol headers to update their state • Routing decisions based on link loss ratios • ETX used instead of minimum hop count • Probabilistic routing modularized • Choice of metric • Choice of metric-to-probability mapping • Choice of routing strategy (random or deterministic) 6.829 Final Project

10. 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 destination-neighbor pair • Probability of forwarding to a certain neighbor in order to reach a desired destination • Requests for information about destinations that this node must make and those that it must answer 6.829 Final Project

11. Protocol Header Contents • Each originated or forwarded packet contains the following protocol-level header: 6.829 Final Project

12. State Update • Nodes update state • Upon sending • Upon receiving • Periodically • Refresh stale state and, if needed, 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 changes in link quality and to nodes entering and leaving the system 6.829 Final Project

13. Probabilistic Routing • Nodes forward probabilistically to neighbor ni with probability pi n1 routingtable p1 = 0.3 p1 = 0.1 x s n2 d x x x p1 = 0.4 link breaks! p3 = 0.7 p3 = 0.5 n3 • Route is not fixed, so packets can still reach destination immediately upon link breakage • Update forwarding probability upon link breakage (nodes see infinite loss ratio on link) 6.829 Final Project

14. Node Joins with HELLO packets n2 n4 n1 n3 6.829 Final Project

15. Protocol in Steady State n2 n4 n1 n3 6.829 Final Project

16. Probabilistic Routing Strategies • Random: node forwards probabilistically to neighbor ni with probability pi • Deterministic: node forwards ALL data packets along path with highest pi • Our flexible infrastructure allows simulation of both • No one else has compared random and deterministic routing 6.829 Final Project

17. Simulation Environment • ns-2 with Monarch wireless and mobility extensions • Compare the new protocol to DSDV, DSR and AODV • 50 mobile nodes in a 1500m x 300m area • Random waypoint movement model • 900s simulation time • Use UDP (CBR) sources • TCP’s inconvenience: conforming load • We investigate different… • Pause times • Node speeds • Connection patterns 6.829 Final Project

18. Measures of Evaluation • Packet delivery ratio / goodput • Packet delivery latency • Routing packet overhead • Total bytes of overhead • Path length optimality • Route acquisition latency 6.829 Final Project

19. Simulation Results • We have built a complete simulation infrastructure, and simulated three protocols for comparison with ours • AODV, DSR, DSDV • We have not finished ironing out the bugs in our protocol implementation • Our protocol simulates for short time… • We loosely expect to finish and simulate by Monday 6.829 Final Project

20. Delivery Ratio vs. Pause Time 10 connections 6.829 Final Project

21. Routing Packets Sent vs. Pause Time 10 connections 6.829 Final Project

22. Routing Packets Sent vs. Number of Connections averaged over all pause times 6.829 Final Project

23. Route Acquisition Latency vs. Pause Time 10 connections 6.829 Final Project

24. Route Acquisition Latency vs. Number Connections averaged over all pause times 6.829 Final Project

25. Conclusions and Future Work • Our routing protocol is feasible (and even nearly done) • We believe randomized routing is competitive with deterministic routing • We will continue our quest to implement and simulate the protocol 6.829 Final Project

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

27. 6.829 Final Project

28. Protocol in Steady State n2 n4 n1 n3 6.829 Final Project