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Position-based Routing in Ad Hoc Networks Brad Stephenson A presentation submitted in partial fulfillment of the requirements of the course ECSE 6962.

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Presentation on theme: "Position-based Routing in Ad Hoc Networks Brad Stephenson A presentation submitted in partial fulfillment of the requirements of the course ECSE 6962."— Presentation transcript:

1 Position-based Routing in Ad Hoc Networks Brad Stephenson A presentation submitted in partial fulfillment of the requirements of the course ECSE 6962

2 Objectives Introduction to position-based routing Discuss location services Discuss specific routing algorithms –Greedy algorithm –Directional flooding algorithm –Hierarchical algorithm Comparison with topology-based algorithms

3 Review Topology-based routing –Uses information about the (virtual) links that exist in a wireless network –Can be: Proactive Reactive Hybrid

4 Position-based Routing Additional information is used to make routing decisions, namely the physical location of the node Decisions made based on destination’s position and position of forwarding node’s neighbors Uses a location service to obtain the location of the destination node

5 Position-based Routing Does not require routing tables Traffic overhead may be small Supports delivery of packets to a geographical area, called geocasting [NI] Three broad categories: –Greedy forwarding –Restricted directional flooding –Hierarchical methods

6 Location Services Centralized location service –Mobile nodes register their position with the location service –The service is contacted when a routing node wishes to find a destination node –Similar to cellular network –Requires that position servers be well-known –Only works with a non-ad-hoc external service

7 Location Services Decentralized location services can be: –All-for-all –All-for-some –Some-for-all –Some-for-some See [MWH]

8 Decentralized Location Services C A D EB G F IDDirectionDistanceTimestamp Node A wants to send an update DREAM [B]

9 Decentralized Location Services C A D EB G F IDDirectionDistanceTimestamp Node A wants to send an update DREAM [B]

10 Decentralized Location Services C A D EB G F DREAM [B] IDDirectionDistanceTimestamp Node A wants to send an update

11 Decentralized Location Services C A D EB G F Spatial Resolution DREAM [B] IDDirectionDistanceTimestamp Node A wants to send an update

12 Decentralized Location Services C A D E G F DREAM [B] B Temporal Resolution

13 Decentralized Location Services C AL E G S Quorum-Based [MWH] H I B J K D The backbone must be set up using a non-position based ad hoc routing mechanism

14 Location information for node A is stored in a virtual homezone The position of the homezone can be found by applying a well-known hash function to the node ID Decentralized Location Services Homezone [MWH]

15 Decentralized Location Services Homezone [MWH] C A D E B G F P

16 Taxonomy of Routing Algorithms [S02]

17 Key Assumptions Unit Disk Graph (UDG) model of physical layer Nodes are in two dimensional space Homogeneous nodes in the network What major limitations do these assumptions expose? Depends on the application

18 Key ideas in Position-based Routing Algorithms [GSB] Loop-freedom Distributed operation Path strategy Metrics Memorization Guaranteed delivery Scalability Robustness

19 Loop-freedom Should be inherently loop-free Avoids recovery strategies –timeout of old packets –memorizing packets that have been seen before

20 Distributed operation Localized algorithms are preferred if performance matches global algorithms Decisions made based on local information Reduced overhead If using n-hop neighbors, can be classified as 2-localized, 3-localized, etc.

21 Path Strategy Single path Flooding Directional Flooding Multipath

22 Metrics Hop count Hop quality Power consumption Policy-based cost Expected hop count (accounts for retransmissions) [S02]

23 Memorization Better to avoid memorizing traffic because of queue size and changes in mobility Required for QoS-guaranteed paths

24 Guaranteed Delivery Delivery rate = # delivered / # sent Guaranteed delivery has delivery rate = 1 To achieve this, we need a MAC protocol which provides retransmit or no collisions

25 Scalability Increase in overhead as number of nodes increases Sometimes a subjective measure

26 Robustness How does mobility affect the algorithm How accurately can we determine the position of the destination

27 Greedy Algorithms Loop free [SL] Localized information Single path strategy Metric: Hop count No memory No guarantee of delivery Scalable, O( sqrt(n) ) [MWH] Somewhat robust

28 Greedy Packet Forwarding 4 S (x, y) = (10, 3) “Send to (10, 3)” R D

29 Greedy Packet Forwarding 4 S Most Forward within R [TK] R 3 D

30 Greedy Packet Forwarding 4 S Nearest with Forward Progress [MWR] R 3 D

31 Greedy Packet Forwarding 4 S 2 D 5 1 Compass Routing [MWR] R 3

32 Greedy Algorithms Most forward within R –Get as far as you can within sender’s range Nearest with forward progress –Makes collisions less likely Compass Routing –Send to nearest neighbor that is directly between sender and receiver

33 Greedy Routing Failure [MWH] Local maximum

34 Recovery Algorithms Greedy Perimeter Stateless Routing Protocol (GPSR) Face-2 algorithm Other variants/combinations Based on traversal of planar graphs Returns to greedy mode when closer to destination than when it entered recovery

35 Recovery Algorithms Construct the planar subgraph [T] Forward the packet along interior face using the right hand rule

36 Recovery Algorithms [MWH]

37 Recovery Algorithms 4 S 2 D Assume communication only occurs along the edges of the planar graph Scan begins at incoming edge

38 Recovery Algorithms 4 S 2 D Assume communication only occurs along the edges of the planar graph Recovery complete! Revert back to greedy mode

39 Restricted Directional Flooding Not loop free Localized operation Path strategy: flooding/multipath Metric: Hop count Memory No guarantee of delivery Not scalable, O(n) [MWH] Not robust

40 Restricted Directional Flooding DREAM and LAR Send packet to all neighbors “in the direction” of D How do we determine this direction?

41 Restricted Directional Flooding DREAM Expected Region [B] Expected Region D R S q

42 Restricted Directional Flooding Needs a recovery mechanism if no neighbor is in the direction of the expected region None specified in DREAM proposal Area of future work DREAM Expected Region [B]

43 Restricted Directional Flooding Uses the idea of restricted flooding toward the expected region for path discovery in non-position-based routing protocols [KV] Location-Aided Routing [KV]

44 Hierarchical Routing Terminodes and Grid Routing Possibly reduces the complexity of information each node has to handle Improves scalability Can ad hoc networks also reap these benefits? Not without tradeoffs!

45 Hierarchical Routing Uses greedy approach for long-distance routing Uses non-position-based approach at the local level (proactive distance vector) Allows non-position-aware nodes to participate More tolerant of position inaccuracy More complex to implement Grid Routing [MWH]

46 Topological vs. Positional Terminodes shown to improve packet delivery rates and overhead compared to reactive ad hoc routing [BGL] GPSR performs better than DSR in almost all criteria including overhead and delivery rate [Br] Both results are from simulations

47 Are there any applications? Vehicle-to-vehicle communication networks Geocasting can be useful for … –Tactical military information –Disaster response –Personalized Internet experience –Home security

48 (IMHO) Very little experimental work done, mostly simulation Assumptions limit the scope, practicality of results Solution: Need more engineering graduate students to conduct experiments

49 Future Work There is a plethora of ideas Quantitative work must be performed Investigate hashing in highly dynamic networks Probabilistic approach Recovery strategies within constraints Deeper hierarchies (3-tier, etc.) What about anonymity?

50 Open Problems Remaining Mobility-caused loops Congestion considerations (replace hop count metric with e2e delay) Quality of Service considerations An excellent recent paper on using a non- UDG model is [SNK]

51 References [B] Basagni, S., et al, A Distance Routing Effect Algoritm for Mobility (DREAM). MOBICOM ’98. [BGL] Blazevic, L., et al, Self Organized Terminode Routing. IEEE Commun. Magazine, [Br] Broch, J., et al, A Performance Comparison of Multi- hop Wireless Ad Hoc Networking Routing Protocols. MOBICOM ’98. [GSB] Giordano, S., et al, Position Based Routing Algorithms for Ad Hoc Networks: A Taxonomy. [KV] Ko, Y.B. and Vaidya, N.H., Location-Aided Routing (LAR) in Mobile Ad Hoc Networks. ACM/Baltzer WINET J., vol. 6, no. 4, [MWH] Mauve, M., et al, A Survey on Position-Based Routing in Mobile Ad Hoc Networks. IEEE Network, November/December 2001.

52 References (cont.) [NI] Navas, J.C. and Imielinski, T., Geographic Addressing and Routing. MOBICOM ’97. [S02] Stojmenovic, I., Position-Based Routing in Ad Hoc Networks. IEEE Commun. Magazine, July [SL] Stojmenovic, I. and Lin, X., Loop-free hybrid single- path/flooding routing algorithms with guaranteed delivery for wireless networks. IEEE Trans. on Parallel and Distributed Systems, Oct [SNK] Stojmenovic, I., et al, Design Guidelines for Routing Protocols in Ad Hoc and Sensor Networks with a Realistic Physical Layer. IEEE Commun. Magazine, March [T] Toussaint, G. The Relative Neighborhood Graph of a Finite Planar Set. Pattern Recognition, vol. 12, no.4, [TK] Takagi, H. and Kleinrock, L., Optimal Transmission Ranges for Randomly Distributed Packet Radio Terminals. IEEE Trans. on Commun., 1984.


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