A Probabilistic Routing Protocol for Enhanced Performance in 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. 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

3. 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

4. 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

5. 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

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

7. The answers! • Control packets are minimized 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 are based on link loss ratios • ETX used instead of minimum hop count • Probabilistic routing is made modular - choice of metric - choice of metric-to-probability mapping - choice of routing strategy (random or deterministic) 6.829 Final Project

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

9. 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 and fulfillments thereof information about destinations 6.829 Final Project

10. 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

11. Probabilistic Routing 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

12. Probabilistic Routing 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 6.829 Final Project

13. 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 allowed simulation of both • First to compare random to deterministic routing 6.829 Final Project

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

15. 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

16. Simulation Results 6.829 Final Project

17. Conclusions and Future Work 6.829 Final Project