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) Throughput (Kbps)

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

Keeping track of on/off nodes Related work SPAN: in a dense environment, multiple subnets which guarantee connectivity are present, can be alternated GAF: area divided in grids so that within each grid any node will do (equivalent for routing)

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 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

Fewer Hops than GAF all distances normalized to the coverage radius

GeRaF vs STEM normalized energy

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 update Predecessor Data flow  Proposed solution: direction forwarding  Distance Vector not robust to mobility

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” 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 “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 Group Landmark

LANMAR (cont) – A packet to “local” destination is routed directly using local tables – A packet to remote destination is routed to Landmark corresponding to logical address – Once the landmark is “in sight”, the direct route to destination is found in local tables. Logical Subnet Landmark

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 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) DFR LANMAR

Performance as a function of speed (cont.) Delivery ratio vs. speed (Excluding packet loss due to disconnected destination) DFR LANMAR

Performance as a function of speed (cont.) Aggregated throughput vs. speed 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)