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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)
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
Introduction MORRP Key Concepts Simulation Results Conclusion
Scalability Layer 3: Network Layer
3
Scaling Networks: Trends in Layer 3
Flood-based Hierarchy/Structured Unstructured/FlatScalable
Mobile Ad hoc /Fixed Wireless Networks
DSR, AODV,TORA, DSDVPartial Flood:OLSR, HSLS
LGF, VRR, GPSR+GLSHierarchical Routing,
Peer to Peer /Overlay Networks
Wired Networks
Gnutella Kazaa, DHT Approaches: CHORD, CAN
OSPF, IEGRP, RIP OSPF Areas
WSR (Mobicom 07)ORRP (ICNP 06)
BubbleStorm (Sigcomm 07)LMS (PODC 05)
Introduction MORRP Key Concepts Simulation Results Conclusion
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Trends: Directional Communications
• 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)
A’
B’
C’
D’
A
B
CD
Omni-directional
A’
B’
C’
D’
A
B
CD
Directional
Directional/Directive Antennas Hybrid FSO / RF MANETS
• 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
Introduction MORRP Key Concepts Simulation Results Conclusion
5
ORRP Big Picture
Up to 69%
A
98%
B
180o
Orthogonal RendezvousRouting Protocol
ST
ORRP Primitive1: Local sense of directionleads to ability to forwardpackets in opposite directions
2: Forwarding alongOrthogonal lines hasa high chance of intersection in area
Introduction Wireless Mesh Networks Mobile Ad-Hoc Networks Overlay Networks
ORRP• High reach (98%),
O(N3/2) State complexity, Low path stretch (~1.2), high goodput, unstructured
• BUT.. What happens with mobility?
65%
55%
42%
IncreasingMobility
6
A
B
What can we do?• Replace intersection
point with intersection region.
• Shift directions of send based on local movement information
• Route packets probabilistically rather than based on rigid next-hop paths. (No need for route maintenance!)
• Solution: a NEW kind of routing table: Directional Routing Table (DRT)
R
Mobile-ORRP (MORRP) Introduction
Introduction MORRP Key Concepts Simulation Results Conclusion
7
J
K
LM
IH
O P
S
N
R
Q
F
C
G
E
A
B
MORRP Basic Example
Original Path
Original Path
OriginalDirection ()
NewDirection()
R: Near Field DRTRegion of Influence
D: Near Field DRTRegion of Influence
S: Near Field DRTRegion of Influence
D
D’
D
R
R’
RS
1. Proactive Element – Generates Rendezvous to Dest Paths2. Reactive Element – Generates Source to Rendezvous Paths
Introduction MORRP Key Concepts Simulation Results Conclusion
8
The Directional Routing Table
DestID
NextHop
DestID
NextHop
BeamID
Dest IDs(% of Certainty)
BeamID
BCD:Z
BBZ:Z
BCD:Z
BBZ:Z
113:3
B(90%), C(30%).Z(90%), D(40%).
1234
BC
ZD
A4
1
2
3
Routing Table RT w/ Beam ID Directional RT (DRT)
ID ID ID set of IDs Set of IDs set of IDs
Routing Tables viewed from Node A
• 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
Use Decaying Bloom Filter (DBF)
Introduction MORRP Key Concepts Simulation Results Conclusion
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DRT Intra-node DecayTime Decay with Mobility Spread Decay with Mobility
7
8
x
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 3 faster than the opposite direction. The information about a node in region 2 should be SPREAD to regions 1 and 3.
a
a
x
Introduction MORRP Key Concepts Simulation Results Conclusion
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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
11
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 OLSR modified to support beam-switched directional antennas.
Introduction MORRP Key Concepts Simulation Results Conclusion
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MORRP: Aggregate Goodput Results• Aggregate Network Goodput vs.
Traditional Routing Protocols MORRP achieves from 10-14X the
goodput of AODV, OLSR, and GPSR w/ GLS with 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
13
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
• MORRP scales 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
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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)• MORRP scales 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
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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 ]• [email protected]
Introduction MORRP Key Concepts Simulation Results Conclusion