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Using Directionality in Mobile Routing. Bow-Nan Cheng ( MIT LL ) Murat Yuksel ( Univ Nevada - Reno ) Shivkumar Kalyanaraman ( IBM IRL ) (Work done at Rensselaer Polytechnic Institute ).
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Using Directionality in Mobile Routing Bow-Nan Cheng (MIT LL) Murat Yuksel (Univ Nevada - Reno) Shivkumar Kalyanaraman (IBM IRL) (Work done at Rensselaer Polytechnic Institute)
Introduction MORRP Key Concepts Simulation Results Conclusion • Infrastructure / Wireless Mesh Networks • Characteristics: Fixed, unlimited energy, virtually unlimited processing power • Dynamism – Link Quality • Optimize – High throughput, low latency, balanced load Motivation Scalability Layer 3: Network Layer • 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 Main Issue: Scalability
Introduction MORRP Key Concepts Simulation Results Conclusion Scaling Networks: Trends in Layer 3 Flood-based Hierarchy/Structured Unstructured/Flat Scalable Mobile Ad hoc / Fixed Wireless Networks WSR (Mobicom 07) ORRP (ICNP 06) DSR, AODV, TORA, DSDV Partial Flood: OLSR, HSLS LGF, VRR, GPSR+GLS Hierarchical Routing, BubbleStorm (Sigcomm 07) LMS (PODC 05) Kazaa, DHT Approaches: CHORD, CAN Peer to Peer / Overlay Networks Gnutella OSPF, IEGRP, RIP OSPF Areas Wired Networks
Introduction MORRP Key Concepts Simulation Results Conclusion Trends: Directional Communications Directional/Directive Antennas Hybrid FSO / RF MANETS B’ B’ B B D’ D’ A D A D C C A’ A’ C’ C’ • Current RF-based Ad Hoc Networks: • omni-directional RF antennas • High-power – typically the most power consuming parts of laptops • Low bandwidth • Error-prone, high losses • Free Space Optics: • High bandwidth • Low Power • Dense Spatial Reuse • License-free band of operation Omni-directional Directional • Directional Antennas – Capacity Benefits • Theoretical Capacity Improvements - factor of 4p2/sqrt(ab) where a and b 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)
Introduction Wireless Mesh Networks Mobile Ad-Hoc Networks Overlay Networks ORRP Big Picture Orthogonal Rendezvous Routing Protocol ORRP Primitive 1:Local sense of direction leads to ability to forward packets in opposite directions A Increasing Mobility • ORRP • High reach (98%), O(N3/2) State complexity, Low path stretch (~1.2), high goodput, unstructured • BUT.. What happens with mobility? 180o 98% 65% S 55% T Up to 69% 42% B 2: Forwarding along Orthogonal lines has a high chance of intersection in area
Mobile-ORRP (MORRP) Introduction • What can we do? • Replace intersection pointwith intersection region. • Shiftdirections of send based on local movement information • Route packets probabilistically rather than based on rigidnext-hop paths. (No need for route maintenance!) • Solution: a NEW kind of routing table: Directional Routing Table (DRT) a A R B Introduction MORRP Key Concepts Simulation Results Conclusion
C B R’ G S A F R Original Path R O P E Q N Original Path M D L D’ I H K J MORRP Basic Example R: Near Field DRT Region of Influence S R Original Direction (a1) S: Near Field DRT Region of Influence New Direction (a2) D D: Near Field DRT Region of Influence • Proactive Element – Generates Rendezvous to Dest Paths • Reactive Element – Generates Source to Rendezvous Paths Introduction MORRP Key Concepts Simulation Results Conclusion
The Directional Routing Table Use Decaying Bloom Filter (DBF) • Soft State – Traditional routing tables have a hard timeout for routing entries. Soft State decreases the level of certainty with time. • Uncertainty with Distance – Nodes closer to a source will have increasingly more information about the location of the source than nodes farther away • Uncertainty with Time – As time goes on, without updates, one will have lesser amount of information about the location of a node • Uncertainty with Mobility – Neighbors can potentially be “covered” by different interfaces based on mobility speed and direction Routing Tables viewed from Node A Routing Table RT w/ Beam ID Directional RT (DRT) Dest ID Next Hop Dest ID Next Hop Beam ID Dest IDs (% of Certainty) Beam ID 4 C B C D : Z B B Z : Z B C D : Z B B Z : Z 1 1 3 : 3 B(90%), C(30%) . Z(90%), D(40%) . 1 2 3 4 B 3 1 A Z 2 D ID ID ID set of IDs Set of IDs set of IDs Introduction MORRP Key Concepts Simulation Results Conclusion
DRT Intra-node Decay Time Decay with Mobility Spread Decay with Mobility a q2 > q1 > q3 q2 7 q3 x x q1 8 a As node moves in direction +x, the certainty of being able to reach nodes covered by region 8 should decay faster than of region 7 depending on speed. This information is DROPPED. As node moves in direction +x, the certainty of being able to reach nodes covered by region 2 should be SPREAD to region 1 and 3faster than the opposite direction. The information about a node in region 2 should be SPREAD to regions 1 and 3. Introduction MORRP Key Concepts Simulation Results Conclusion
N N N N N N N N N N N N N N N N N N N MORRP Fields of Operation • Near Field Operation • Uses “Near Field DRT” to match for nodes 2-3 hops away • Far Field Operation • RREQ/RREP much like ORRP except nodes along path store info in “Far-Field DRT” S R D Introduction MORRP Key Concepts Simulation Results Conclusion
Performance Evaluation of MORRP • Metrics Evaluated • Reachability – Percentage of nodes reachable by each node in network (Hypothesis: high reachability) • Delivery Success – Percentage of packets successfully delivered network-wide • Scalability – The total state control packets flooding the network (Hypothesis: higher than ORRP but lower than current protocols out there) • Average Path Length • End to End Delay (Latency) • Aggregate Network Goodput • Scenarios Evaluated (NS2) • Evaluation of metrics vs. AODV (reactive), OLSR (proactive), GPSR with GLS (position-based), and ORRP under various node velocities, densities, topology-sizes, transmission rates. • Evaluation of metrics vs. AODV and OLSRmodified to support beam-switched directional antennas. Introduction MORRP Key Concepts Simulation Results Conclusion
MORRP: Aggregate Goodput Results • Aggregate Network Goodputvs.Traditional Routing Protocols • MORRPachieves from10-14Xthe goodput ofAODV,OLSR, andGPSRw/GLSwith an omni-directional antenna • Gains come from the move toward directional antennas (more efficient medium usage) • Aggregate Network Goodput vs. AODV and OLSR modified with directional antennas • MORRP achieves about 15-20% increase in goodput vs. OLSR with multiple directional antennas • Gains come from using directionality more efficiently Introduction MORRP Key Concepts Simulation Results Conclusion
MORRP: Simulations Summary • MORRP achieves high reachability (93% in mid-sized, 1300x1300m2 and 87% in large-sized, 2000x2000 m2 topologies) with high mobility (30m/s). • With sparser and larger networks, MORRP performs fairly poorly (83% reach) suggesting additional research into proper DRT tuning is required. • In lightly loaded networks, MORRP end-to-end latency is double of OLSR and about 7x smaller than AODV and 40x less than GPSR w/ GLS • MORRPscales well by minimizing control packets sent • MORRP yields over 10-14X the aggregate network throughput compared to traditional routing protocols with one omnidirectional interface gains from using directional interfaces • MORRP yields over 15-20%the aggregate network goodput compared to traditional routing protocols modified with 8 directional interfaces gains from using directionality constructively Introduction MORRP Key Concepts Simulation Results Conclusion
MORRP: Key Contributions • The Directional Routing Table • A replacement for traditional routing tables that routes based on probabilistic hints • Gives a basic building block for using directionality to overcome issues with high mobility in MANET and DTNs • Using directionality in layer 3 to solve the issues caused by high mobility in MANETs • MORRP achieves high reachability (87% - 93%) in high mobility (30m/s) • MORRPscales well by minimizing control packets sent • MORRP shows that high reach can be achieved in probabilistic routing without the need to frequently disseminate node position information. • MORRP yields high aggregate network goodput with the gains coming not only from utilizing directional antennas, but utilizing the concept of directionality itself. • MORRP is scalable and routes successfully with more relaxed requirements (No need for coordinate space embedding) Introduction MORRP Key Concepts Simulation Results Conclusion
Thank You! • Questions and Comments? • Papers / Posters / Slides / NS2 Code (MORRP, ORRP, OLSR + AODV with Beam switched directional antennas) [ http://networks.ecse.rpi.edu/~bownan ] • bownan@gmail.com Introduction MORRP Key Concepts Simulation Results Conclusion