Rendezvous-Based Directional Routing:

A Performance Analysis

Bow-Nan Cheng (RPI)Murat Yuksel (UNR)

Shivkumar Kalyanaraman (RPI)

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

Scaling Networks: Trends in Layer 3

Flood-based Hierarchy/Structured Unstructured/FlatScalable

Mobile Ad hoc /Wireless InfrastructureNetworks

DSR, AODV,TORA, DSDV

OLSR, HSLS, LGFHierarchical Routing,VRR, GPSR+GLS

Peer to Peer /Overlay Networks

Wired Networks

Gnutella Kazaa, DHT Approaches: CHORD, CAN

Ethernet Routers (between AS)

WSR

SEIZE

Trends: Directional Antennas

Directional Antennas – Capacity Benefits Theoretical Capacity Improvements - factor of

42/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)

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-OpticalAd 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

ORRP Big Picture

Up to 69%

A

98%

B

180o

Orthogonal RendezvousRouting Protocol

ST

ORRP Primitive- Local sense of directionleads to ability to forwardpackets in opposite directions

Multiplier AngleMethod (MAM) Heuristic to handle voids, angle deviations, and perimeter cases

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: ~1.21x4 ~ 3.24

B

57%

By adding lines, can we decrease path stretch

and increase reach probability without

paying too much penalty?

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 (180o) 2 Lines (90o) 3 Lines (60o)

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)

Path Stretch Analysis

Path Stretch vs. Number of Lines – Numerical Analysis

1 Line (180o) 2 Lines (90o) 3 Lines (60o)

Circle (Radius 10m) 3.854 1.15 1.031

Square (10mx10m) 4.004 1.255 1.039

Rectangle (25mx4m) 4.73 3.24 1.906

Grid (No Bounds) 1.323 1.125 1.050

Path stretch decreases with addition

of lines but not as dramatically as

between 1 and 2 lines (No angle correction)

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

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

Numerical Analysis vs. Simulations

Reach Probability (Num Analysis w/o MAM vs. Sims w/ Avg. Density)

1 Line (180o) 2 Lines (90o) 3 Lines (60o)

Topology Boundaries Analysis Sims Analysis

Sims Analysis Sims

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 (180o) 2 Lines (90o) 3 Lines (60o)

Topology Boundaries Analysis Sims Analysis

Sims Analysis Sims

Square 4.004 1.54 1.255 1.272 1.039 1.21

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 Eval Total Packet Latency Eval

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 Success Aggregate Network Goodput

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.

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.

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