1. Network Kernel Architectures and Implementation (01204423) Routing
Chaiporn Jaikaeo
Department of Computer Engineering Kasetsart University
Materials taken from lecture slides by Karl and Willig

2. Overview Unicast routing in MANETs Energy efficiency & unicast routing
Multi-/broadcast routing
Geographical routing

3. Unicast, ID-Centric Routing
Given: a network/a graph
Each node has a unique identifier (ID)
Goal: Send a packet from one node to another
The routing & forwarding problem
Routing: Construct a table telling how can reach a given destination
Forwarding: Consult this table to forward a given packet to its next hop
Challenges

4. Challenges in WSNs/MANETs
Nodes may move around, neighborhood relations change
Optimization metrics may be more complicated
Not just “smallest hop count” B C A

5. Ad hoc Routing Protocols
Because of challenges, standard routing approaches not really applicable
Too big an overhead, too slow in reacting to changes
Examples: Dijkstra, Bellman-Ford
Simple solution: Flooding
No routing table needed
Packets are usually delivered to destination
But: overhead is prohibitive
Usually not acceptable in most cases

6. Gossiping Needs no routing table
Similar to flooding
Nodes forward packets with some probability
Haas et al. studies gossiping behavior and found that
There is a critical probability, x
p < x: gossip dies out very quickly
p > x: gossip reaches most nodes

7. Routing Protocol Classification
Main question: When does the routing protocol operate?
Option 1: Always tries to keep routing data up-to-date
Protocol is proactive / table-driven
Option 2: Route is only determined when actually needed
Protocol operates on demand
Option 3: Combine these behaviors
Hybrid protocols

8. Routing Protocol Classification
Which data is used to identify nodes?
An arbitrary identifier?
The position of a node?
Can be used to assist in geographic routing protocols
Identifiers that are not arbitrary, but carry some structure?
As in traditional routing
Structure akin to position, on a logical level?

9. Proactive Protocols – Example
Fisheye State Routing (FSR)
Basic observation: When destination is far away, details about path are not relevant
Look at the graph as if through a fisheye lens
Regions of different accuracy of routing information
LS information about closer nodes is exchanged more frequently

10. Reactive Protocols – Example
Recall reactive routing protocols
Initially, no information about next hop is available at all
One possibility: Send packet to everyone
Hope: At some point, packet will reach destination and an answer is sent pack – use this answer for backward learning the route from destination to source
Examples
Ad hoc On-demand Distance Vector (AODV)
Dynamic Source Routing (DSR)

11. DSR Dynamic Source Routing protocol
Use separate route request/route reply packets to discover route
Data packets only sent once route has been established
Discovery packets smaller than data packets
Store routing information in the discovery packets

12. Search for route from 1 to 5
DSR Route Discovery
Search for route from 1 to 5
[1] 1 7 6 5 3 4 2
[1,7]
[1,4] 2 1
[1] 7 5 4 3 6 1 7 6 5 3 4 2
[1,7,2]
[1,4,6]
[1,7,3] 1 7 6 5 3 4 2
[5,3,7,1]
Node 5 uses route information recorded in RREQ to send back, via source routing, a route reply

13. AODV Ad hoc On-demand Distance Vector Very popular routing protocol
Same basic idea as DSR for discovery procedure
Nodes maintain routing tables instead of source routing

14. Alternative - Rumor Routing
Think of an “agent” wandering through the network, looking for data/events
Agent initially perform random walk
Leave “traces” in the network
Later agents can use these traces to find data ?

15. Overview Unicast routing in MANETs Energy efficiency & unicast routing
Multi-/broadcast routing
Geographical routing

16. Energy-Efficient Unicast: Goals
Minimize energy/bit
Eg., A-B-E-H
Maximize network "lifetime"
Time until first node failure
loss of coverage
partitioning 4 A 2 3 1 C 1 2 B 3 D 2 1 2 E 4 F 2 3 2 G 1 2 4 H 2
Example: Send data from node A to node H

17. Basic options for path metrics
Max total available battery capacity
Sum of batt. levels without needless detours
Example: A-C-F-H
Min battery cost
Sum of reciprocal battery levels
Example: A-D-H
Min-Max batt. cost
Largest reciprocal level of all nodes in path
Minimize variance in power levels 4 A 2 3 1 C 1 2 B 3 D 2 1 2 E 4 F 2 3 2 G 1 2 2 4 H

18. Overview Unicast routing in MANETs Energy efficiency & unicast routing
Multicast/broadcast routing
Geographical routing

19. Broadcast & Multicast
Distribute a packet to all reachable nodes (broadcast) or to a subgroup (multicast)
Basic options
Source-based tree: one tree per source
Minimize total cost
Minimize maximum cost to each destination
Shared, core-based trees
Mesh
Provides redundancy in data transfer

20. Goals for Source-Based Trees
For each source, minimize total cost
The Steiner tree problem
For each source, minimize maximum cost to each destination
Obtained by overlapping the individual shortest paths
Steiner tree
Src
Dest 2 2 2 1
Dest 1
Shortest-path tree
Src
Dest 2 2 2 1
Dest 1

21. Broadcast/Multicast Classification
Mesh
Shared tree (core-based tree)
Single core
Multiple core
One tree per source
Minimize total cost (Steiner tree)
Minimize cost to each node (e.g., Dijkstra)

22. Wireless Multicast Advantage
Wires
Locally distributing a packet to n neighbors
n times the cost of a unicast packet
Wireless: sending to n neighbors can incur costs
= tx to a single neighbor – if receive costs are ignored
= One tx, n rx – if receives are correctly tuned
= send n unicasts – if multicast not supported by MAC
If local multicast is cheaper, then wireless multicast advantage is present
Can be assumed realistically

23. Steiner Tree Approximations
Computing Steiner tree is NP complete
A simple approximation
Pick some arbitrary order of all destination nodes + source node
Successively add these nodes to the tree
For every next node, construct a shortest path to some other node already on the tree
Performs reasonably well in practice

24. Steiner Tree Approximations
Takahashi Matsuyama heuristic
Similar, but let algorithm decide which is the next node to be added
Start with source node, add that destination node to the tree which has shortest path
Iterate, picking that destination node which has the shortest path to some node already on the tree
Problem: Wireless multicast advantage not exploited!
And does not really fit to the Steiner tree formulation

25. Broadcast Incremental Power
Or BIP
Exploits multicast wireless advantage
Goal: use as little transmission power as possible
Based on Prim's MST algorithm
Once a node transmits and reaches some neighbors, it becomes cheaper to reach additional neighbors

26. BIP – Example S A B C D 1 5 3 7 10 Round 1: S (1) A B C D 4 3 7 2 1 96 7
Round 4:
S (5) A B
C (1) D 3 7 10
Round 5:

27. Multicast Incremental Power
Or MIP
Start with broadcast tree construction, then prune unnecessary edges out of the tree A A 3 3 S B S B 10 10 7 7 D D C C

28. Mesh-Based Multicast
Example – ODMRP (On-Demand Multicast Routing Protocol)
Sender
NextHop H
Sender
NextHop H C C A H D E
Sender
NextHop H D B G F I

29. Overview Unicast routing in MANETs Energy efficiency & unicast routing
Multi-/broadcast routing
Geographical routing
Position-based routing
Geocasting

30. Geographic Routing
Implicitly infer routing information from physical placement of nodes
E.g., position of current node, current neighbors, destination known
Send to a neighbor in the right direction as next hop
Geographic routing
Position-based routing
 Use position information to aid in routing
Geocasting
 Send to any node in a given area

31. Overview Unicast routing in MANETs Energy efficiency & unicast routing
Multi-/broadcast routing
Geographical routing
Position-based routing
Geocasting

32. Position-Based Routing
“Most forward within range r” strategy
Send to that neighbor that realizes the most forward progress towards destination
Nearest node with forward progress
Idea: Minimize transmission power
Directional routing
Choose next hop that is angularly closest to destination
Choose next hop that is closest to the connecting line to destination
Problem: Might result in loops!

33. Problem: Dead Ends
Simple strategies might send a packet into a dead end

34. Right Hand Rule
Basic idea to get out of a dead end: Put right hand to the wall, follow the wall
Does not work if on some inner wall – will walk in circles
Need some additional rules to detect such circles

35. Right Hand Rule – GPSR Greedy Perimeter Stateless Routing
Use greedy, “most forward” routing as long as possible
If no progress possible: Switch to “face” routing
Face: largest possible region of the plane that is not cut by any edge of the graph
Send packet around the face using right-hand rule
Use position where face was entered and destination position to determine when face can be left again, switch back to greedy routing
Requires: planar graph! (topology control can ensure that)

36. Face Routing Example

37. GPSR – Example Route packet from node A to node Z Enter next faceI B K F H Z A D
Enter face routing J L G C

38. Overview Unicast routing in MANETs Energy efficiency & unicast routing
Multi-/broadcast routing
Geographical routing
Position-based routing
Geocasting

39. Location-based Multicast (LBM)
Geocasting by geographically restricted flooding
Define a “forwarding” zone – nodes in this zone will forward the packet to make it reach the destination zone
Packet is always forwarded by nodes within the destination zone itself

40. Determining Next Hops
Use Voronoi diagram
Destination Zone B C S D A

41. Determining Next Hops
Use convex hulls
Destination Zone C B D S A E

42. Conclusion
Routing exploit various sources of information to find destination of a packet
Routing can make some difference for network lifetime
Non-standard routing tasks (multicasting, geocasting) require adapted protocols