1. An Implementation Framework for Trajectory-Based Routing in Ad Hoc Networks Murat Yuksel, Ritesh Pradhan, Shivkumar Kalyanaraman Electrical, Computer, and Systems Engineering Department Rensselaer Polytechnic Institute, Troy, NY

2. June 22, 2004 IEEE ICC’04 2 Outline Motivation Overview of Trajectory-Based Routing (TBR) Bezier Curves for TBR Forwarding Algorithms for TBR Long/Complex Trajectories Contributions Future Work

3. June 22, 2004 IEEE ICC’04 3 Motivation Wireless ad hoc networks An emerging part of our technology, e.g. laptops, PDAs, watches, cars, … Very scarce resources e.g. capacity, power, memory Traffic engineering requires flexibility in routing: Multi-path capability Major issues: Ad hoc nature of nodes Mobility Dynamic topology causes continuous update to routing tables. TE is essential for ad hoc networks Proactive routing does NOT work! TE in ad hoc networks require new routing building blocks

4. June 22, 2004 IEEE ICC’04 4 Motivation (cont’d) Why TBR is a viable routing building block for TE? Multi-path capability in a wireless, multi-hop, ad hoc environment Possible application to p2p with virtual geographic locations

5. June 22, 2004 IEEE ICC’04 5 Motivation (cont’d) Application-specific requirements particularly important for sensor networks Area of interest: Take pictures of the lake Measure temperature around an experimental area Area of disinterest: Route secure info around the unsafe area Route more traffic around the congested area

6. June 22, 2004 IEEE ICC’04 6 Overview of TBR Source Routing (SR): Source inserts all the route into each packet, e.g. SBR, DSR. Very flexible for applications, but causes too large packet headers. Greedy Routing (GR): Each packet is forwarded to the neighbor closest to the destination, e.g. FACE, Greedy Perimeter Stateless Routing (GPSR), Cartesian Routing (CR). Fixed-size, short packet headers, but not flexible for applications. Trajectory-Based Routing (TBR): Proposed by a group from Rutgers University. Represents the whole path as a parametric curve and encodes it into each packet.

7. June 22, 2004 IEEE ICC’04 7 Overview of TBR (cont’d) TBR is a geographic routing protocol, and requires a positioning service TBR is a middle-ground between SR and GR. Since a parametric curve can form any path (e.g. circle, straight line, curly lines), it gives more flexibility for the source to define the path. – similar to SR Since the intermediate nodes decode the trajectory, they do not have to keep state. – similar to GR Source Routing i.e. flex, large header Greedy Routing i.e. no header or state, but no flex Trajectory-Based Routing

8. June 22, 2004 IEEE ICC’04 8 Overview of TBR (cont’d) So, how does it work? What happens when a packet travels in the network? S D DATA How to encode the trajectory into packets’ headers?

9. June 22, 2004 IEEE ICC’04 9 source destination Control pt -2 Control pt -1 Bezier Curves for TBR Can we use Bezier curves? Cubic Bezier curves: 2 control pts + source + destination easy to handle. Represented in parametric form: t is the time parameter. Q(0) is the source point Q(1) is the destination point

10. June 22, 2004 IEEE ICC’04 10 Bezier Curves for TBR (cont’d) If (x 0,y 0 ), (x 1,y 1 ), (x 2,y 2 ) and (x 3,y 3 ) are known, then the constant vectors A, B & C can be calculated as: Given that: Each packet header contains locations of source (x 0,y 0 ), destination (x 3,y 3 ) and control points (x 1,y 1 ), (x 2,y 2 ). Each node maintains neighbor table. So, when a packet arrives, each node: Decodes the trajectory by performing the above calculations Figures out which neighbor to forward the packet, based on forwarding strategy. What is a viable forwarding strategy?

11. June 22, 2004 IEEE ICC’04 11 Forwarding Algorithms for TBR Terminology: d i = closest distance of node N i to the curve t i = time parameter at the point where node N i is closest to the curve – time of node N i The time t i of node N i can also be interpreted as projection of the node on the curve. neighbor of N i = nodes that are in transmission range of N i and have a time greater than t i.

12. June 22, 2004 IEEE ICC’04 12 Forwarding Algorithms for TBR (cont’d) Closest-To-Curve (CTC) - to the neighbor with smallest distance to the curve. Least Advancement on Curve (LAC) – to the neighbor with smallest time on the curve. Random - randomly forward to one the neighbors

13. June 22, 2004 IEEE ICC’04 13 Forwarding Algorithms for TBR (cont’d) Several other algorithms are possible.. CTC-LAC – to the neighbor with smallest time but also stands within a predefined distance from the curve. Most Advancement on Curve (MAC) – to the neighbor with largest time. CTC-MAC – to the neighbor with highest time but also stands within a predefined distance from the curve. Failure cases are possible..

14. June 22, 2004 IEEE ICC’04 14 Forwarding Algorithms for TBR (cont’d) Failure of LAC

15. June 22, 2004 IEEE ICC’04 15 Forwarding Algorithms for TBR (cont’d) Failure of CTC and MAC

16. June 22, 2004 IEEE ICC’04 16 Forwarding Algorithms for TBR (cont’d) Lowest Deviation from Curve (LDC) – node forwards to its neighbor with lowest deviation from curve. Deviation = deviated area from the curve per unit curve distance, i.e.:

17. June 22, 2004 IEEE ICC’04 17 Forwarding Algorithms for TBR (cont’d) Lowest Deviation from Curve (LDC) – Area calculations are computationally intensive. Can be approximated by numerical techniques. Slice the area by parallel lines – similar to Riemann Sums in numerical integration

18. June 22, 2004 IEEE ICC’04 18 Simulation Results NS-2 Area – 250mX500m Different trajectories: Circular Zigzag No mobility yet

19. June 22, 2004 IEEE ICC’04 19 Simulation Results (cont’d) Deviation from the circular trajectory

20. June 22, 2004 IEEE ICC’04 20 Simulation Results (cont’d) Normalized path length on the circular trajectory

21. June 22, 2004 IEEE ICC’04 21 Simulation Results (cont’d) Deviation from the zigzag trajectory

22. June 22, 2004 IEEE ICC’04 22 Long/Complex Trajectories How to encode long/complex curves? longer curve  larger packet header IP 1 IP 2 Split the curve into simpler pieces: Each piece could be represented by a cubic Bezier curve The complete trajectory is concatenation of the pieces. Source performs signaling and sends a control packet that include: end locations of the cubic Bezier curves, i.e. Intermediate Point (IP) all the control points The nodes closest to the IPs will be the Special Intermediate Nodes (SINs). D S I1I1 I2I2

23. June 22, 2004 IEEE ICC’04 23 Long/Complex Trajectories How to encode long/complex curves? longer curve  larger packet header IP 1 IP 2 D S I1I1 I2I2 SINs (i.e. I 1, I 2 ) do special forwarding. Store the next Bezier curve’s control points Update the packet headers with that of the next Bezier curve’s control points C1 C2 C3 C4 C5 C6 S D C5 C6 C3 C4 IP 2 S D

24. June 22, 2004 IEEE ICC’04 24 Contributions Our contributions: An architecture to deploy TBR for long/complex trajectories. A locally optimal forwarding strategy: Lowest Deviation from Curve (LDC) A method of encoding/decoding trajectories by using Cubic Bezier curves. A simulation-based evaluation of several forwarding strategies.

25. June 22, 2004 IEEE ICC’04 25 Future Work Our ongoing work on TBR: A testbed deployment in RPI-CWN. Calculation of optimal curve to avoid certain spots. Finding optimal route for a given trajectory with global topology knowledge. Future work on TBR: Optimal split of long/complex trajectories. Analysis of the signaling overhead in mobile environments. Hybrid trajectory encoding techniques: frequency and space-time Resilience techniques for different forwarding strategies.

26. June 22, 2004 IEEE ICC’04 26 Thank you! THE END