1. Opportunistic Routing in Multi-hop Wireless Networks*
A. Zubow
Sanjit Biswas and Robert Morris, SIGCOMM 2005,
pdos.csail.mit.edu/papers/roofnet:exor-sigcomm05/roofnet_exor-sigcomm05.pdf

2. Traditional wireless routing
Abstraction
wireless radio looks like a link
wireless network looks like a graph
Routing protocol computes shortest paths on graph
Routing protocols: AODV, DSR, TORA, DSDV, OLSR
Link metrics: hop count, ETX, ETT, WCETT
packet
packet A B
src
dst
packet C 2

3. Radios aren’t wires Every packet is broadcast
src
dst 1 1 1 1 2 2 2 2 3 3 3 3 4 4 4 4 5 5 5 5 6 6 6 6 C
Every packet is broadcast
Reception is probabilistic 3

4. Basic Idea In wireless networks,
use of channel diversity => better performance
e.g., time diversity, spatial diversity, frequency diversity
Probabilistic reception of a single broadcast at different receivers provides such a form of diversity. 4

5. Key idea Delayed binding of next hop
Node broadcasts packet
No next hop specified
Due to probabilistic reception, different receiver nodes may/may not receive packet
Receiver “closest” to destination becomes the next hop, i.e., it will forward the packet towards destination. 5

6. Key idea A B src dst C packet packet packet packet packet packet6

7. Why this might work …
src N1 N2 N3 N4 N5
dst
75%
50%
25%
Assumes probability falls off gradually with distance
Best traditional route over 50% hops: 3(1/0.5) = 6 tx
Throughput  1/# transmissions
ExOR exploits lucky long receptions: 4 transmissions 7

8. Why this might work … Assume independent losses
25%
100% N2
25%
100%
src
dst
25%
100% N3
25%
100% N4
Assume independent losses
Traditional routing: 1/ = 5 tx
ExOR: 1/(1 – (1 – 0.25)4) + 1 = 2.5 transmissions 8

9. Challenges in protocol design
Agreement protocol: nodes must agree on the subset of them that received the packet
Scheduling protocol: to minimize collisions between different nodes by avoiding simultaneous transmission
Efficiency in forwarding: node “closest” to destination that receives packet should become forwarder
Only nodes that are really useful should participate 9

10. ExOR batching Send batches of packets for efficiency
rx: 53
rx: 85
rx: 99
rx: 40
rx: 22
rx: 23
rx: 57
rx: 88
rx: 0 N2 N4
tx: 0 `
tx:  12
tx: 100
tx: 34
src
dst N1 N3
tx: 31
tx: 23
Send batches of packets for efficiency
Node closest to the dst sends first
Other nodes listen, send remaining packets in turn
Repeat schedule until dst has whole batch 10

11. Protocol Design: Outline
Source sends packets in batches
Source includes a priority list of forwarders, ordered by “distance” to destination in every packet header.
Scheduling: Lower priority nodes wait for higher priority nodes before transmitting.
A “batch map” is used for agreement: indicates the highest priority node that has received each packet
included in the packet header
updated from higher priority nodes back towards lower priority nodes
provides an acknowledgement 11

12. Protocol Design Layer 2.5 solution Batching: BatchSz BatchID PktNum
Scheduling: FragNum FragSz
Agreement: Batch Map 12

13. Priority ordering of forwarders
src
dst N1 N3
Goal: nodes “closest” to the destination send first
Sort by (modified) ETX metric to dst
Nodes periodically flood ETX “link state” measurements
Path ETX is weighted shortest path (Dijkstra’s algorithm)
Source sorts and includes list in ExOR header 13

14. Digression: ETX primer
Measurement of link ETX metric:
Measure forward probability of loss pf using periodic HELLO packets
Then, ETX = 1/pf
If the link is i.i.d Bernoulli with loss probability pf, then ETX = expected number of retransmissions for success.
Path ETX = sum of link ETX along path
Can be computed using Djikstra or Bellman Ford 14

15. Digression: ETX primer15

16. Batch-map: Reliable summaries
tx: {2, 4, , 98}
summary: {1,2,6, , 98, 99} N2 N4
src
dst N1 N3
tx: {1, 6, , 96, 99}
summary: {1, 6, , 96, 99}
Repeat summaries in every data packet in a batch map
Cumulative: what all previous nodes rx’d
This is a gossip mechanism for summaries
Propagate batch map back from destination to sender 16

17. Scheduling Goal: only one node sends at a time Src sends entire batch
Dst sends 10 empty packets with batch maps
Then highest priority node starts transmitting whatever it has received
Other nodes: on receiving pkt, update batch map and
estimate sending rate of current sender
use FragSz and FragNum to estimate sender’s time to completion
Assume (in absence of information) that each higher priority node transmits at least 5 packets
Schedule repeats after lowest priority node transmits. 17

18. Scheduling 18

19. Some more protocol details …
Towards the end of a batch,
overhead of scheduling and agreement spread out over fewer packets
Send last 10% of packets of a batch using traditional routing
Too many forwarders = high overhead
Source runs a ExOR simulation at the beginning and only chooses those nodes which transmitted over 10% of packets 19

20. Using ExOR with TCP
Web Server
Client PC
TCP
ExOR Batches (not TCP)
Node
Gateway
Proxy
Web
Proxy
ExOR
Batching requires more packets than typical TCP window 20

21. Evaluation Details
1 kilometer 21

22. Evaluation Details Traditional Routing ExOR
Click router user-space implementation
Directly tx and rx raw Ethernet frames: libpcap like interface
IEEE b, Intersil Prism 2.5 chipset, 200mW transmit power, pseudo-IBSS
65 Node pairs
1.0MByte file transfer
1 Mbps bit rate
1 KByte packets
Link loss measurements used to compute ETX metric offline
Traditional Routing
ExOR
unicast with link-level retransmissions
Hop-by-hop batching
UDP, sending as MAC allows
broadcasts
100 packet batch size 22

23. 25 Highest throughput pairs
3 Traditional Hops 2.3x
More opportunities for making progress
2 Traditional Hops
1.7x
1 Traditional Hop 1.14x
Batch maps ACKs are more robust and efficient
1000
ExOR
800
Traditional Routing
600
Throughput (Kbits/sec)
400
200
Node Pair 23

24. 25 Lowest throughput pairs
1000
ExOR
4 Traditional Hops
3.3x
800
Traditional Routing
600
Throughput (Kbits/sec)
400
200
Node Pair
Longer Routes
ExOR can use longer asymmetric links 24

25. Throughput improves by 200%!!25

26. Packets that fall short help!26

27. Packets that travel further help!27

28. ExOR moves packets farther
58% of Traditional Routing transmissions
0.6
ExOR
Traditional Routing
Fraction of Transmissions
0.2
25% of ExOR transmissions
0.1
100
200
300
400
500
600
700
800
900
1000
Distance (meters)
ExOR average: 422 meters/transmission
Traditional Routing average: 205 meters/tx 28

29. Discussion Late binding of next hop is similar to selection diversity
RTS to multiple potential receivers
Decide “best one” after receiving CTS
Another example of diversity use is “opportunistic scheduling”
Different users have different channels
Send to the user with the best channel
Cellular downlink scheduling, OAR 29

30. Discussion Implicit design assumptions:
Carrier sense is good enough
RTS/CTS handshake does not buy us much more
Spatial reuse gain is negligible
scheduling protocol ensures only one node to transmit at a time
All of these assumptions are satisfied when
mesh networks are small and don’t have too many high hop-count paths 30

31. Discussion Scheduling in ExOR ensures that
higher priority nodes transmit earlier than lower priority nodes
prevents collisions between transmissions of the same flow
No inter-flow collision avoidance is done
I don’t think there are easy ways to handle the scheduling problem in this case 31

32. Discussion
Scheduling may lead to
collisions
priority inversion 32

33. Discussion For long routes, unicast comparison is unfair
hop by hop unicast transmissions does not do any spatial reuse
In IEEE settings, there will be some throughput boost due to spatial reuse
No multiple flow evaluations are carried out. 33

34. Conclusion
ExOR uses a form of selection diversity to bind the next hop only after receiving the current packet
Radio is not a wire: treat it as a broadcast medium instead
ExOR gives 2x throughput improvement
ExOR implemented on Roofnet 34