Orthogonal Rendezvous Routing Protocol for Wireless Mesh Networks Bow-Nan Cheng Murat Yuksel Shivkumar Kalyanaraman

By removing position information, can we still efficiently route packets? Motivation L3: Geographic Routing using Node IDs (eg. GPSR, TBF etc.) L2: ID to Location Mapping (eg. DHT, GLS etc.) L1: Node Localization ORRP N/A Issues in Position-based Schemes S N WE (0,4) (4,6) (5,1) (8,5) (12,3) (15,5)S D D(X,Y)? ?

Motivation – Multi-directional Transmission Methods Multi-directional AntennasTessellated FSO Transceivers Directional communications Model needed for ORRP 45 o 22.5 o

ORRP Introduction Up to 69% A B 98% Assumptions  Neighbors are assigned a direction  Local Sense of Direction Ability to Transmit/Receive Directionally Directional, smart antennas FSO transceivers

ORRP Design Considerations  Considerations: High probability of connectivity without position information [Reachability] Scalability O(N 3/2 ) total state information maintained. (O(N 1/2 ) per node state information) Even distribution of state information leading to no single point of failure [State Complexity] Handles voids and sparse networks  Trade-offs Path Stretch Probabilistic Reachability

ORRP Proactive and Reactive Elements Node C Fwd Table DestNextCostDir AB2120 o DD1230 o Node B Fwd Table DestNextCostDir AA190 o A B C D 1.ORRP Announcements (Proactive) – Generates Rendezvous node-to-destination paths ORRP Route REQuest (RREQ) Packets (Reactive) ORRP Route REPly (RREP) Packets (Reactive) 4. Data path after route generation 4 4

Deviation Correction: Multiplier Angle Method (MAM) Concept 180 o =45 o 45 o = 180 o -90 o =- A B C D E F G Multiplier (m) Desired Angle Received Angle Loop Prevention Actual Tx Angle Interface Separation Angle Deviation Angle New Multiplier (m)

Void  min(+4  6   =  +  4  m = +2 S R  min(+4   =  +  m = +3  min(+4   =  +  m = 0  min(+4  4   =  +  4  m = +2  min(+4  4   =  +  4  m = +3 Multiplier Angle Method (MAM) Examples Basic Example VOID Navigation/Sparse Networks Example  min(+4  6   =  +  4  m = +2

ORRP Void Navigation – differences from GPSR perimeter routing  ORRP seeks only intersections between destination ORRP packets and source ORRP packets – increased flexibility  MAM is an inherent nature of ORRP and not a special case that switches on and off like GPSR perimeter routing  ORRP does not require location-id mappings as GPSR does

Performance Evaluation of ORRP  Metric Reachability – Percentage of nodes reachable by each node in network (Hypothesis: high reachability) State Complexity – The total state information needed to be maintained in the network (Hypothesis: O(N 3/2 )) Path Stretch – Average ORP Path vs. Shortest Path (Hypothesis: Low path stretch)  Analysis (without MAM) Reachability Upper Bound State Information Maintained at Each Node Average Path Stretch  Packetized Simulation Scenarios Evaluated Effect of MAM on reachability Effect of finer-grained directionality Total state complexity and distribution of state

Reachability Numerical Analysis P{unreachable} = P{intersections not in rectangle} 4 Possible Intersection Points %99.75% 57% 67.7% Probability of Unreach highest at perimeters and corners NS2 Simulations with MAM show around 99% reachability

ORRP Perimeter Issue  Perimeter/Corner Nodes – Corner nodes have higher probability of orthogonal line intersections outside of topology bounding region

Path Stretch Analysis Average Stretch for various topologies Square Topology – Circular Topology – X 4 Rectangular – 3.24 Expected Stretch – x = 1.255x = 1.15 x = 3.24

State Complexity Analysis/Simulations GPSRDSDVXYLSORRP Node StateO(1)O(n 2 )O(n 3/2 ) ReachabilityHigh 100%High (99%) Name ResolutionO(n log n)O(1) InvariantsGeographyNoneGlobal Comp.Local Comp. ORRP state scales with Order N 3/2 ORRP states are distributed fairly evenly (no single pt of failure)

Reachability – Finer Grained Directionality (NS2 Simulations)  Observations/Discussions For sparse networks, reachability increases dramatically as number of interfaces increases. This is due to more node choices to effectively route paths Non-complete reachability even with MAM due to network “fingers” Finer-grained interface spread have increased effectiveness in sparse networks to a point Finer-grained interface spread increases reach in networks with voids

Additional Results (in brief)  MAM increases reachability to almost 100% even in rectangular topologies in NS2 simulations  Path stretch with MAM stays relatively constant even with finer granularity of antenna spread (discounting unreach)  Numerical Simulation of “additional lines” yields very little REACH and PATH STRETCH gain while adding a lot of additional state

Summary  ORRP achieves high reachability in random topologies  ORRP achieves O(N 3/2 ) state maintenance – scalable even with flat, unstructured routing  ORRP achieves low path stretch (Tradeoff for connectivity under relaxed information is very small!)

Future Work  Mobile ORRP (MORRP)  Hybrid Direction and Omni-directional nodes  More detailed abstraction to 3-D  Route loop prevention  ORRP for peer to peer networks requires the concept of locally consistent virtual direction Thanks! Questions or Comments:

Affect of Control Packet TTL on Varying Network Densities (NS2)  Observations/Discussions Reachability increases heavily when TTL is increased from 2 to 7 but stays roughly constantly with continued increases (Saturation Pt.) Total States increases dramatically from setting a TTL of 2 to 7 and then stays constant Average path length remains unchanged with TTL Reach increases until Saturation Pt with increase in TTL Total States increases until Saturation Pt with increase in TTL Average Path Length Remains constant with varying TTL

Additional Lines Study  Observations / Discussions Probability of reach is not increased dramatically with addition of lines above “2” Path stretch is decreased with addition of lines but not as dramatically as between “1” and “2” Total States maintained is increased heavily with increase in number of lines

Motivation – 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 Directional – secure, more effective use of medium 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

State Complexity – Varying Number of Interfaces (NS2 Simulations)  Observations/Discussions Total States increases with the number of nodes in the network (expected) Total states is not very dependent on the number of interfaces Increase in Total States maintained consistent with increased reachability (more states = more reachability)

Stretch – Average Path Length vs. Varying Interfaces (NS2 Simulations)  Observations/Discussions As node density increases, path length increases as next hop nodes are chosen at random from the nodes within the transmission range + LOS. With more nodes, there is more choices of “closer nodes” Average Path Length improves for dense networks with more interfaces. More interfaces increases granularity and limits node selection

ORRP Introduction Assumptions  Neighbor Discovery 1-hop neighbors Given direction/interface to send packets to reach each neighbor  Local Sense of Direction  Ability to Transmit/Receive Directionally Directional, smart antennas FSO transceivers

Deviation Correction: Multiplier Angle Method (MAM) Number of Interfaces  The angle node received packets from Received Angle () The angle node received packets from Deviation Angle () The angle to add/subtract that previous node deviated from desired angle when sending Desired Angle () The desired angle to send out Found Angle () The angle of transceiver found with neighbor closest to desired angle Separation Angle () The angle of separation between each transceiver Multiplier (m) The value to multiply  by to find new desired angle Important Notes: 1.Only corrections outside of antenna spread considered 2.MAM assumes that relative distances from one hop to another are relatively equal 3.All deviation correction done at RREQ and ORRP Announcement level (not on each transmission)

ORRP Packet Deviation Issue  Sending in orthogonal directions increases likelihood of intersections (Single line: 69% intersection vs. Orthogonal Lines: 98% intersection)  Packet deviation potentially lowers the likelihood of intersections (ie: if packets end up traveling in parallel paths)  Question: How can we maintain straight paths as much as possible without adding too much overhead to the system?

Thanks! Can directionality be used at Layer 3? YES!