1. Rendezvous-Based Directional Routing: A Performance Analysis Bow-Nan Cheng (RPI) Murat Yuksel (UNR) Shivkumar Kalyanaraman (RPI)

2. Motivation Main Issue: Scalability Infrastructure / Wireless Mesh Networks Characteristics: Fixed, unlimited energy, virtually unlimited processing power Dynamism – Link Quality Optimize – High throughput, low latency, balanced load Mobile Adhoc Networks (MANET) Characteristics: Mobile, limited energy Dynamism – Node mobility + Link Quality Optimize – Reachability Sensor Networks Characteristics: Data-Centric, extreme limited energy Dynamism – Node State/Status (on/off) Optimize – Power consumption

3. Scaling Networks: Trends in Layer 3 Flood-basedHierarchy/StructuredUnstructured/Flat Scalable Mobile Ad hoc / Wireless Infrastructure Networks DSR, AODV, TORA, DSDV OLSR, HSLS, LGF Hierarchical Routing, VRR, GPSR+GLS Peer to Peer / Overlay Networks Wired Networks Gnutella Kazaa, DHT Approaches: CHORD, CAN Ethernet Routers (between AS) WSR SEIZE

4. Trends: Directional Antennas  Directional Antennas – Capacity Benefits Theoretical Capacity Improvements - factor of 4 2 /sqrt() where  and  are the spreads of the sending and receiving transceiver ~ 50x capacity with 8 Interfaces (Yi et al., 2005) Sector Antennas in Cell Base Stations – Even only 3 sectors increases capacity by 1.714 (Rappaport, 2006) Directional Antennas – Simulations show 2-3X more capacity (Choudhury et al., 2003)

5. Trends: Hybrid FSO/RF MANETs  Current RF-based Ad Hoc Networks: 802.1x with omni-directional RF antennas High-power – typically the most power consuming parts of laptops Low bandwidth – typically the bottleneck link in the chain Error-prone, high losses Free-Space-Optical (FSO) Communications Mobile Ad Hoc Networking High bandwidth Low power Dense spatial reuse License-free band of operation Mobile communication Auto-configuration Free-Space-Optical Ad Hoc Networks Spatial reuse and angular diversity in nodes Low power and secure Electronic auto-alignment Optical auto-configuration (switching, routing) Interdisciplinary, cross-layer design

6. ORRP Big Picture Up to 69% A 98% B 180 o Orthogonal Rendezvous Routing Protocol S T ORRP Primitive - Local sense of direction leads to ability to forward packets in opposite directions Multiplier Angle Method (MAM) Heuristic to handle voids, angle deviations, and perimeter cases

7. Motivation A 98% Metrics:  Reach Probability  Path Stretch / Average Path Length  Total States Maintained  Goodput  End-to-End Latency Scenarios Evaluated:  Various Topologies  Various Densities  Various Number of Interfaces  Various Number of Connections  Transmission Rates  Comparison vs. AODV, DSR Path Stretch: ~1.2 1x4 ~ 3.24 B 57% By adding lines, can we decrease path stretch and increase reach probability without paying too much penalty?

8. Reachability Numerical Analysis P{unreachable} = P{intersections not in rectangle} 4 Possible Intersection Points 1 2 3 Reach Probability vs. Number of Lines – Numerical Analysis 1 Line (180 o )2 Lines (90 o )3 Lines (60 o ) Circle (Radius 10m)58.33%99.75%100% Square (10mx10m)56.51%98.30%99.99% Rectangle (25mx4m)34.55%57%67.61% Probability of reach does not increase dramatically with addition of lines above “2” (No angle correction)

9. Path Stretch Analysis Path Stretch vs. Number of Lines – Numerical Analysis 1 Line (180 o )2 Lines (90 o )3 Lines (60 o ) Circle (Radius 10m)3.8541.151.031 Square (10mx10m)4.0041.2551.039 Rectangle (25mx4m)4.733.241.906 Grid (No Bounds)1.3231.1251.050 Path stretch decreases with addition of lines but not as dramatically as between 1 and 2 lines (No angle correction)

10. NS2 Sim Parameters/Specifications  All Simulations Run 30 Times, averaged, and standard deviations recorded Number of Lines Amount of State Maintained Reach Probability Average Path Length Goodput End-to-End Latency Number of Control Packets

11. Effect of Number of Lines on Various Topologies and Network Densities Sparse - 90% - 99% Medium – 95.5% - 99% Dense - 98% - 99% Medium - 66% - 93% Sparse - 63% - 82% Reach Probability increases with addition of lines but not as dramatically as between 1 and 2 lines Average Path Length decreases with addition of lines under similar conditions. APL increases in rectangular case because of higher reach of longer paths

12. Numerical Analysis vs. Simulations Reach Probability (Num Analysis w/o MAM vs. Sims w/ Avg. Density) 1 Line (180 o )2 Lines (90 o )3 Lines (60 o ) Topology Boundaries AnalysisSimsAnalysisSimsAnalysisSims Square 56.51%95.3%98.30%99.5%99.99%99.8% Rectangle 34.55%66.7%57%84.5%67.61%91.1% Angle Correction with MAM increases reach dramatically! Path Stretch (Num Analysis w/o MAM vs. Simulations) 1 Line (180 o )2 Lines (90 o )3 Lines (60 o ) Topology Boundaries AnalysisSimsAnalysisSimsAnalysisSims Square 4.0041.541.2551.2721.0391.21

13. Effect of Network Density Average Path Length decreases for increased number of lines in ORRP but still longer than shortest path protocols Total end to end Latency decreases for increased number of lines in ORRP. This is significantly better than DSR and AODV Average Path Length EvalTotal Packet Latency Eval

14. Effect of Number of Connections and CBR Rate Delivery Success increases for increased number of lines but remains constant with number of CBR connections Aggregate Network Goodput increases for increased number of lines. It is about 20-30X more network goodput than DSR and AODV Packet Delivery SuccessAggregate Network Goodput

15. Additional Simulation Results  Network Voids Average path length fairly constant (Reach and State not different)  Number of Interfaces Increasing # of interfaces per node yields better results for reach, average path length, and average goodput to a certain point determined by network density.  Number of Continuous Flows Average path length remains fairly constant with increased flows but increases with less lines. The average is still higher than AODV and DSR path lengths.  Control Packets Control packets sent by ORRP with multiple lines are significantly more than with AODV and DSR because ORRP is hybrid proactive and reactive so CP increase with time. But because medium is used more efficiently, goodput remains high.

16. Summary  Addition of lines yields significantly diminishing returns from a connectivity-state maintenance/control packets perspective after 1 line  Addition of lines yields better paths from source to destination and increases goodput  Using Multiplier Angle Method (MAM) heuristic, even only 1 line provides a high degree of connectivity in symmetric topologies  Addition of lines yields better aggregate godoput overall and about 20x more goodput than DSR and AODV  Increasing the number of interfaces per node yields better results for reachability, average path length, and average goodput up to a certain point that is determined by network density  As number of continuous flows increase, ORRP with increased lines delivers more packets successfully.

17. Future Work  Mobile ORRP (MORRP)  Hybrid Direction and Omni-directional nodes  Exploring additional heuristics to maintain straight-line paths  Expanding to overlay networks (virtual directions) Thanks! Questions or Comments: chengb@rpi.edu