Proposed ad hoc Routing Approaches
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Transcript of Proposed ad hoc Routing Approaches
Proposed ad hoc Routing Approaches• Conventional wired-type schemes (global
routing, proactive):– Distance Vector; Link State
• Proactive ad hoc routing:– OLSR, TBRPF
• On- Demand, reactive routing:• DSR (Source routing), MSR • AODV (Backward learning)
• Scalable routing :– Hierarchical routing: HSR, Fisheye– OLSR + Fisheye– LANMAR (for teams/swarms)
• Geo-routing: • GPSR, GeRaF, etc• Motion assisted routing• Direction Forwarding
Georouting - Key Idea
• Each node knows its geo-coordinates (eg, from GPS or Galileo)
• Source knows destination geo-coordinates; it stamps them in the packet
• Geo-forwarding: at each hop, the packet is forwarded to the neighbor closest to destination
• Options:– Each node keeps track of neighbor
coordinates– Nodes know nothing about neighbor
coordinates
Greedy Perimeter Stateless Routing for Wireless Networks (GPSR)
– key elements• Greedy forwarding
– Each nodes knows own coordinates– Source knows coordinates of destination– Greedy choice – “select” the most forward
node
Finding the most forward neighbor
• Beaconing: periodically each node broadcasts to neighbors own {MAC ID, IP ID, geo coordinates}
• Each data packet piggybacks sender coordinates
• Alternatively (for low energy, low duty cycle ops) the sender solicits “beacons” with “neighbor request” packets
Greedy Perimeter Forwarding
D is the destination; x is the node where the packet enters perimeter mode; forwarding hops are solid arrows;
Got stuck? Perimeter forwarding
> Greedy forwarding failure. x is a local maximum in its geographic proximity to D; w and y are farther from D.> Node x’s void with respect to destination D
GPSR vs DSR
TCP over GPSR, AODV, DSR and DSDV
Speed(m/s)
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Congestion Aware GPSR
Hot spot
Problem:Congestion area will cause long packet delay and
high loss probability Our approach:1. Go around the congestion area will decrease the delay,
but detour path is usually longer than the shortest path. Going through the long path will cause throughput loss.
2. Study packet delay, the tradeoff between congestion detour and throughput gain.
GPSR commentary• Very scalable:
– small per-node routing state – small routing protocol message complexity– robust packet delivery on densely deployed,
mobile wireless networks• TCP is extremely sensitive to path breakage
(timeout) -- It does very well with georouting• Outperforms DSR and AODV• Drawback: it requires knowledge of dest geo
coordinates (explicit forwarding node address)– Beaconing overhead– nodes may go to sleep (on and off) in
sensor networks
Geographic Random Forwarding (GeRaF)
- Forwarding in a Large Sensor Net• Nodes in turns go to sleep and wake
up, source does not know which nodes are on/off
• Source cannot explicitly address the next hop, must randomly select
• ideally, the best available node to act as a relay is chosen
• this selection is done a posteriori, i.e., after the transmission has taken place
• it is a receiver contention scheme
GeRaF: Key Idea
Goal: pick the relay closest to the destination broadcast message is sent, all active nodes within range receive it contention phase takes place: nodes closer to the destination are likely to win the winner becomes itself the source
Practical Implementation• major problem: how to pick the best relay?• solution: partition the area and pick relays
from slice closest to the destination• nodes can determine in which region they are• nodes in highest priority region contend first
Contention Resolution
• Assume 802.11 RTS/CTS
• Source transmits RTS with source and destination coordinates
• Stations in priority region #1 are solicited
• If none responds, stations in region #2 are solicited
Conclusions
• nodes who receive a message volunteer and contend to act as relays
• advantages: good for sensor net
– no need for complicated routing tables or routing-related signaling
– near-optimal multihop behavior, much better than alternative solutions (eg GAF, SPAN)
– significant energy/latency gains if nodes are densely deployed
Mobility assisted routing
• Mobility (of groups) was helpful to scale the routing protocol – see LANMAR
• Can mobility help in other cases?– Destination discovery (if coordinates not
know)– Mobility induced distributed
route/directory tree• Ref: H. Dubois Ferriere et al. ”Age Matters:
Efficient Route discovery in Mobile Ad Hoc Networks Using Encounter ages, Mobihoc 2003
Mobility Diffusion and “last encounter” routing
• Imagine a roaming node “sniffs” the neighborhood and learns/stores neighbors’ IDs
• Roaming node carries around the info about nodes it saw before
• Instead of searching for the destination, the source node searches for any intermediate node that encountered the destination more recently than did the source node itself.
• The intermediate node then searches for a node that encountered the destination yet more recently, and the procedure iterates until the destination is reached.
Mobility Diffusion and “last encounter” routing (cont.)
• If nodes move randomly and uniformly in the field (and the network is dense), there is a trail of nodes – like pointers – tracing back to each ID
• The superposition of these trails is a tree – it is a routing tree (to send messages back to source); or a distributed directory system (to map node ID to geo-coordinates, for example)
• “Last encounter” routing: next hop is the node that last saw the destination
Fresh algorithm – H. Dubois Ferriere, Mobihoc 2003
Mobility induced, distributed embedded route/directory tree
Benefits:
• (a) avoid overhead of periodic advertising of node location (eg, Landmark routing)
• (b) reduce flood search O/H (to find ID)
• (c ) avoid registration to location server (to DNS, say)
Issue:
• Motion pattern impact (localized vs random roaming)
“Direction” forwarding for mobile, large scale ad hoc networks
• In Distance Vector Routing (e.g., Bellman Ford, AODV etc.) node keeps pointer to “predecessor”
• When the predecessor moves, the path is broken • Alternate paths, even when available, are not used
Sink
Source
DV updatePredecessorData flow
Proposed solution: direction forwarding
Distance Vector not robust to mobility
Dest
Source
Primary PredecessorPrimary Path
Direction to Dest
Alternate Data Path
DV Update
Direction Forwarding
• Distance Vector update creates not only “predecessor”, but also “direction” entry
• Select “most productive” neighbor in forward direction
• If the network is reasonably dense, the path is salvaged
How to compute the “direction” Need “stable” local orientation system (say,
virtual compass) to determine direction of update Local (rather than global) reference is
required; Local reference system must be refreshed
fast enough to track avg local motion GPS will do (e.g., neighbors exchange (X, Y)
coordinates) If GPS not available, several non-GPS
coordinate systems have been recently published Sextant [Mobihoc ’05]; beacon DV; RFID’s
etc
Computing the “direction”(cont)
Compute “direction” to a destination when DV updates are received: If a DV update packet with a more recent
Seq # or smaller hop distance is received: New “direction” replaces the old one
The “direction” to the predecessor is used as the “direction” to the destination
If multiple DV updates received from different “predecessors” with same hop distance and seq # for the destination Take vector sum of directions
Computation of the “direction”
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)()(
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YYXXr
Computation of the “direction”
Where the polar angle is the radian from the x-axis that is used as the direction of the predecessor node.
Suppose node A receives DV update packets from B & C
Compute the “directions” to predecessors node B & C, respectively,
A
C
B),( bb r
),( cc r
)1,( c
)1,( b
d
“Direction” to a destination
Unit vectors are used to combine the two “directions”
Directions to predecessors
Direction Forwarding vs Geo routing
• Geo-routing:– Direction points to destination– This direction may be unfeasible (holes, etc)– Global geo-coordinates (eg, GPS)– Geo Location Server– Robust to mobility
• Direction Forwarding– Direction of updates (always feasible)– Local (not global) position reference system– Advertisements from destination– Robust to mobility
Case study: apply Direct Forwarding (DFR) to LANMAR Routing
• LANMAR builds upon existing routing protocols– (1) “local ” routing algorithm that keeps
accurate routes within local scope < k hops (e.g., OLSR, FSR)
– (2) Landmark routes advertised to all mobiles using a Distance Vector approach
Logical GroupLogical Group
LandmarkLandmark
LANMAR +DFR
• LANMAR has proved to be very scalable to size
• However, as speed increases, performance degrades, even with group mobility!
• Problem was traced to failure of DV route advertising in high mobility
• We first tried to refresh more frequently: it did not work!
• Next step: try DFR
Simulation Experiments• Simulator: QualNet 3.8
– Standard IEEE 802.11 radio with a channel rate of 2Mbps and transmission range of 367 meters.
– Network field size: 2250m by 2250m• LANMAR is the protocol “hosting” DFR
– 225 nodes (or 360 nodes) equally distributed in 9 groups
– Mobility model: Group Mobility model• Traffic: CBR, 1 packets/sec, 512 bytes/packet
– The # of source-destination pairs is varied in the simulations to vary the offered traffic load
Performance as a function of speed
Delivery ratio vs. speed (Including packet loss due to disconnected
destination)
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Del
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LANMAR(225 nodes)
DFR(225 nodes)
LANMAR(360 nodes)
DFR(360 nodes)
DFR
LANMAR
Conclusions and Future Work
• DFR: new forwarding strategy for table driven routing
• Direction Forwarding can improve LANMAR performance dramatically at high speeds
• Future Work:– Test DFR under local reference system– Apply DFR concept to AODV - Hybrid– TCP over {LANMAR, AODV} + DFR – Compare DFR with other backup route
schemes– Test DFR under more general mobility
models
Robust Ad Hoc Routing for Lossy Wireless Environment
• Challenges for routing in mobile ad hoc network
– Route breakage
– High BER
– Scalability
• The shortcomings of on-demand routing
• Not scalable for mobility
• The shortcomings of proactive routing
• Constant and high routing overhead
• The shortcomings of current Geo-routing
• Need Geo-Location Service, GLS
• “Face routing” is inefficient
Hybrid Routing: AODV-DFR
(AODV with Directional Forwarding Routing) • Combines on-demand and proactive routing
– When a source starts comm, it first finds the destination as in an on-demand fashion
– Once the destination is notified, it initiates periodic routing updates in a proactive fashion
• Utilizing an alternate path instantly based on “direction” to the destination if a path fails– resemblance with Georouting in the update
message– No location server system is required (not
like GPSR)
AODV-DFR
• Source initiates route discovery a la AODV – Destination, or any node that has a route,
replies– The path is set up
• Destination begins proactive advertisements (a la DV) after receiving data pkts from source – Intermediate nodes rebroadcast ads– Only for active connections– Period increases with distance from
destination (Fisheye concept)• Packet routing assisted by Direction Forward• The destination stops advertisement if it does
not receive pkts for some time
Performance Evaluation
• Compare AODV, AODV-DFR, GPSR and ADV (proactive and on-demand Hybrid Routing)– Performance: Delivery ratio, Packet delay,
Routing Overhead– Mobile & lossy network: UDP and TCP traffic
• Mobility Speed• Packet loss: uniformly distributed on a link
• Simulation– 100 nodes randomly moving in 1000x1000m– The traffic pairs are randomly distributed
over the network– UDP flows: pkt size 512 bytes, rate 1pkt/sec– TCP flows: NewReno, pkt size 1460 bytes
Mobile Network: Delivery Ratio
80 UDP flows
Mobile Network: Packet delay
80 UDP flows
Mobile Network: Routing Overhead
80 UDP flows
Mobile & Lossy Network: Delivery Ratio
UDP Flow number: 80 Mobility Speed: 10 m/s
Mobile & Lossy Network: Routing Overhead
UDP Flow number: 80 Mobility Speed: 10 m/s
TCP in Mobile Network
40 TCP flows
TCP in Mobile & Lossy Network
TCP flow number: 40 Mobility: 10 m/s
AODV-DFR Contributions
• A hybrid routing: proactive + on-demand• Robust to mobility and packet loss• Utilize location information for directional
forwarding with only local updates.• Low overhead• Provide better performance than AODV and
GPSR• Enhances AODV• Competitive with GPSR (does not require
“global” positioning such as GPS)• Ongoing work: local coordinate system;
integration of local and global coordinates (indoor+outdoor)