1. Network Routing: Link Metrics and Non-Traditional Routing
Y. Richard Yang
2/26/2009

2. Admin. Homework 3 Project proposal:
March 6 by to and

3. Recap: Routing Protocols
Proactive protocols
distance vector
e.g., DSDV
link state
link reversal
e.g., partial link reversal, TORA
Reactive (on-demand) protocols
DSR
AODV A E D C B F 2 1 3 5

4. Recap: ETX
ETX: The predicted number of data transmissions required to successfully transmit a packet over a link
Link loss rate = p
Expected number of transmissions

5. ETX Performance
DSDV
DSR

6. Problems of ETX ETX does not handle multirate 802.11 networks
ETX does not work out well when nodes have multiple radios that can operate at different channels

7. Extending ETX: Multirate
In a multirate environment, need to consider link bandwidth:
packet size = S, Link bandwidth = B
each transmission lasts for S/B
Multirate
Multradio
“Routing in Multi-radio, Multi-hop Wireless Mesh Network,” Richard Draves, Jitendra Padhye, and Brian Zill. Mobicom 2004.

8. Extending ETX: Multirate
Add ETTs of all links on the path
Use the sum as path metric
Interpretation: pick a path with the lowest total network occupation time
Q: under what condition is SETT the network occupation time?

9. Problem of SETT
In networks with multiple channels/radios, SETT does not consider channel reuse
Path
SETT
Throughput
Red-Red
Red-Blue
2.66 ms
3 Mbps
2.66 ms
6 Mbps

10. Observation Interference reduces throughput
throughput of a path is lower if many links are on the same channel
path metric should be worse for non-diverse paths

11. Extending SETT for Multiple Channels
Group links on a path according to channel
assumes links on the same channel interfere with one another
pessimistic for long paths
Add ETTs of links in each group
Find the group with largest sum (BG-ETT)
this is the “bottleneck” group
too many links, or links with high ETT (“poor quality” links)
Use this largest sum as the path metric
Lower value implies better path

12. BG-ETT Example Path Blue Sum Red Sum BG-ETT Throughput All-red 1 Blue
5.33 ms
5.33 ms
1.5 Mbps
1.33 ms
4 ms
4 ms
2 Mbps
2.66 ms
2.66 ms
2.66 ms
3 Mbps

13. BG-ETT May Select Long Paths

14. Path Metric: Putting it all together
SETT favors short paths
BG-ETT favors channel diverse paths
β is a tunable parameter
Higher value: more preference to channel diversity
Lower value: more preference to shorter paths

15. Implementation and such
Implemented in a source-routed, link-state protocol, Multi-Radio Link Quality Source Routing (MR-LQSR)
Nodes discover links to its neighbors, measure quality of those links
link information floods through the network
each node has “full knowledge” of the topology
sender selects “best path”
packets are source routed using this path
Measure loss rate and bandwidth
loss rate measured using broadcast probes similar to ETX
updated every second
bandwidth estimated using periodic packet-pairs
updated every 5 minutes

16. Evaluations

17. Median Throughput (Baseline, single radio)

18. Median Throughput (Baseline, two radios)

19. Impact of β value

20. Summary
Link metrics are still an active research area, in particular, due to interactions with (channel, spatial) diversity

21. Summary: Traditional Routing
So far, all routing protocols in the framework of traditional wireline routing
a graph representation of underlying network
point-to-point graph, edges with costs
select a lowest-cost route for a src-dest pair
commit to a specific route before forwarding
each node forwards a received packet as it is to next hop
Problems: don’t fully exploit path (spatial) diversity and wireless broadcast opportunities

22. Motivating Scenario: I

23. Motivating Scenario: II
Motivating question: can we take advantage of transmissions that reach unexpectedly far or unexpectedly short?
Traditional routing picks a single route, e.g., src -> B -> D -> dst
Packets received off path are useless

24. Motivating Scenario: III
Src A sends 1 packet to dst B; src B sends packet 3 to dst A
The network needs to transmit 4 packets
Motivating question: can we do better? A R B

25. Motivating Scenario: III
If R has both packets 1 and 3, it can combine them and explore coding and broadcast nature of wireless A B R

26. Outline Admin. Link metrics Non-traditional routing motivation
network coding: exploiting network broadcast

27. Network Coding We have covered source coding (FEC, compression)
The new approach uses opportunistic network coding
goal: increase the amount of information that is transported

28. Opportunistic Coding: Basic Idea
Each node looks at the packets available in its buffer, and those its neighbors’ buffers
It selects a set of packets, computes the XOR of the selected packets, and broadcasts the XOR

29. Opportunistic Coding

30. Outline Admin. Link metrics Non-traditional routing motivation
network coding: exploiting network broadcast
opportunistic routing

31. Key Issue in Opportunistic Routing
Key Issue: opportunistic forwarding may lead to duplicates.

32. Extreme Opportunistic Routing (ExOR)
Basic idea: avoid duplicates by scheduling
Instead of choosing a fix sequential path (e.g., src->B->D->dst), the source chooses a list of forwarders (a forwarder list in the packets) using ETX-like metric
a background process collects ETX information via periodic link-state flooding
Forwarders are prioritized by ETX-like metric to the destination

33. ExOR: Forwarding Group packets into batches
The highest priority forwarder transmits when the batch ends
The remaining forwarders transmit in prioritized order
each forwarder forwards packets it receives yet not received by higher priority forwarders
status collected by batch map

34. Batch Map
Batch map indicates, for each packet in a batch, the highest-priority node known to have received a copy of that packet

35. ExOR: Example N2 N0 N3 N1

36. ExOR: Stopping Rule
A nodes stops sending the remaining packets in the batch if its batch map indicates over 90% of this batch has been received by higher priority nodes
the remaining packets transferred with traditional routing

37. Evaluations 65 Node pairs 1.0MByte file transfer
1 Mbit/s bit rate
1 KByte packets
EXOR bacth size 100
1 kilometer

38. Evaluation: 2x Overall Improvement
1.0
0.8
0.6
Cumulative Fraction of Node Pairs
0.4
0.2
ExOR
Traditional
spend a little more time on the 240 x say this is just for the median, and it’s a factor of 2!
200
400
600
800
Throughput (Kbits/sec)
Median throughputs: Kbits/sec for ExOR,
121 Kbits/sec for Traditional

39. OR uses links in parallel
possible question – why are there only 7 forwarders.(just say we thin out...)
ExOR
7 forwarders
18 links
Traditional Routing
3 forwarders
4 links

40. OR moves packets farther
58% of Traditional Routing transmissions
0.6
ExOR
Traditional Routing
Fraction of Transmissions
0.2
25% of ExOR transmissions
0.1
lower is better. right circle – using lots of longer links, sum them up and it’s 25%. so, like ex 1, using lots of long links. zeros: before many packets made no progress, with exor at least some.
100
200
300
400
500
600
700
800
900
1000
Distance (meters)
ExOR average: 422 meters/transmission
Traditional Routing average: 205 meters/tx

41. Comments: ExOR Pros Cons
takes advantage of link diversity (the probabilistic reception) to increase the throughput
does not require changes in the MAC layer
can cope well with unreliable wireless medium
Cons
scheduling is hard to scale in large networks
overhead in packet header (batch info)
batches increase delay

42. Outline Admin. Link metrics Non-traditional routing motivation
network coding: exploiting network broadcast
opportunistic routing
ExOR
MORE

43. MORE: MAC-independent Opportunistic Routing & Encoding
Basic idea:
Replace node coordination with network coding
Trading structured scheduler for random packets combination
Previous network coding technique is for inter-flow
MORE is for intra-flow network coding

44. Basic Idea: Source Chooses a list of forwarders (e.g., using ETX)
Breaks up file into K packets (p1, p2, …, pK)
Generate random packets
MORE header includes the code vector [cj1, cj2, …cjK] for coded packet pj’

45. Basic Idea: Source

46. Basic Idea: Forwarder Check if in the list of forwarders
Check if linearly independent of new packet with existing packet
Re-coding and forward

47. Basic Idea: Destination
Decode
Send ACK back to src if success

48. Key Practical Question: How many packets does a forwarder send?
Compute zi: the expected number of times that forwarder i should forward each packet

49. Computes zs
Єij: loss probability of the link between i and j
Compute zs so that at least one forwarder that is closer to destination is expected to have received the packet :

50. Compute zj for forwarder j
Only need to forward packets that are
received by j
sent by forwarders who are further from destination
not received by any forwarder who is closer to destination

51. Compute zj for forwarder j
To guarantee at least one forwarder closer to d receives the packet

52. Evaluations 20 nodes distributed in a indoor building
Path between nodes are 1 ~ 5 hops in length
Loss rate is 0% ~ 60%; average 27%

53. Throughput

54. Problem of MORE?

55. Mesh Networks API So Far
Forward correct packets to destination
PHY/LL
Deliver correct packets

56. 570 bytes; 1 bit in 1000 incorrect
Motivation R1
10-3 BER 0% S D 0%
10-3 BER R2
570 bytes; 1 bit in 1000 incorrect
 Packet loss of 99%

57. Opportunistic Routing  50 transmissions
Implication R1
99% (10-3 BER)
Loss 0% S D
Loss 0%
99% (10-3 BER) R2
Opportunistic Routing  50 transmissions

58. Outline Admin. Link metrics Non-traditional routing motivation
network coding: exploiting network broadcast
opportunistic routing
ExOR
MORE
MIXIT

59. New API PHY + LL Deliver correct symbols to higher layer Network
Forward correct symbols to destination

60. What Should Each Router Forward?P1 P1 P2 R2 P2 P1 P2

61. What Should Each Router Forward?P1 P2 P1 P1 P2 R2 P2 P1 P2 P1 P2
Forward everything  Inefficient
Coordinate  Unscalable

62. Symbol Level Network CodingP1 P2 P1 R2 P2 P1 P2
Forward random combinations of correct symbols

63. Symbol Level Network Coding… … D R2 … …
Routers create random combinations of correct symbols

64. Symbol Level Network Coding… D R2 …
Solve 2
equations
Destination decodes by solving linear equations

65. Symbol Level Network Coding… … D R2 … …
Routers create random combinations of correct symbols

66. Symbol Level Network Coding… D R2 …
Solve 2
equations
Destination decodes by solving linear equations

67. Destination needs to know which combinations it received
Use run length encoding
Original Packets
Coded Packet

68. Destination needs to know which combinations it received
Use run length encoding
Original Packets
Coded Packet

69. Destination needs to know which combinations it received
Use run length encoding
Original Packets
Coded Packet

70. Destination needs to know which combinations it received
Use run length encoding
Original Packets
Coded Packet

71. Destination needs to know which combinations it received
Use run length encoding

72. Evaluation Implementation on GNURadio SDR and USRP
Zigbee (IEEE ) link layer
25 node indoor testbed, random flows
Compared to:
Shortest path routing based on ETX
MORE: Packet-level opportunistic routing

73. Throughput Comparison
CDF
2.1x
MIXIT 3x
MORE
Shortest Path
Throughput (Kbps)

74. Backup Slides

75. Motivation for a Better Metric

76. Implementation and such
Modify DSDV or DSR
Example evaluation:
in DSDV w/ ETX, route table is a snapshot taken at end of 90 second warm-up period
in DSR w/ ETX, source waits additional 15 sec before initiating the route request

77. Where do the gains come from?
CDF
MIXIT without
concurrency
1.5x
MORE
Shortest Path
Throughput (Kbps)
Take concurrency away from MIXIT

78. Where do the gains come from?
CDF
MIXIT
MORE
Shortest Path
Throughput (Kbps)
Take concurrency away from MIXIT