Proposed ad hoc Routing Approaches

1. 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

2. 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

3. 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

4. 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

5. Greedy Perimeter Forwarding D is the destination; x is the node where the packet enters perimeter mode; forwarding hops are solid arrows;

6. 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

7. GPSR vs DSR

8. TCP over GPSR, AODV, DSR and DSDV Throughput (Kbps) Speed(m/s)

9. Hot spot Congestion Aware GPSR Problem: Congestion area will cause long packet delay and high loss probability Our approach: • 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. • Study packet delay, the tradeoff between congestion detour and throughput gain.

10. 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

11. 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

12. 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

13. Practical Implementation • major problem: how to pick the best relay? • solution: partition the area and pick relays from sliceclosest to the destination • nodes can determine in which region they are • nodes in highest priority region contend first

14. 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

15. 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

16. 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

17. 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.

18. 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

19. Fresh algorithm – H. Dubois Ferriere, Mobihoc 2003

20. 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)

21. DV update Predecessor Data flow Source Sink “Direction” forwarding for mobile, large scale ad hoc networks • Distance Vector not robust to mobility • 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 • Proposed solution: direction forwarding

22. 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

23. 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

24. 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

25. “Direction” to a destination C A B Computation of the “direction” Suppose node A receives DV update packets from B & C • Compute the “directions” to predecessors node B & C, respectively, Where the polar angle is the radian from the x-axis that is used as the direction of the predecessor node. Directions to predecessors Computation of the “direction” • Unit vectors are used to combine the two “directions”

26. 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

27. Logical Group Landmark 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

28. 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

29. 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

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

31. 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

32. 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

33. 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)

34. 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

35. 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

36. Mobile Network: Delivery Ratio 80 UDP flows

37. Mobile Network: Packet delay 80 UDP flows

38. Mobile Network: Routing Overhead 80 UDP flows

39. Mobile & Lossy Network: Delivery Ratio UDP Flow number: 80 Mobility Speed: 10 m/s

40. Mobile & Lossy Network: Routing Overhead UDP Flow number: 80 Mobility Speed: 10 m/s

41. TCP in Mobile Network 40 TCP flows

42. TCP in Mobile & Lossy Network TCP flow number: 40 Mobility: 10 m/s

43. 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)