1. Opportunistic Routing in Multi-hop Wireless Networks
*This material is mainly borrowed from authors and partially modified by the presenter
Opportunistic Routing in Multi-hop Wireless Networks
Sanjit Biswas and Robert Morris
MIT CSAIL
packet -> transmission (careful)
Presented by Ying Huang
CS598Hou
3/10/2006

2. ExOR: a New Approach to Routing in Multi-hop Wireless Networks
mention last year we talked about low level link performance
1 kilometer
Dense based mesh
Goal is high-throughput and capacity

3. Initial Approach: Traditional Routing
packet
packet A B
src
dst
packet C
just say picks a route, fwd over that route
Identify a route, forward over links
Abstract radio to look like a wired link

4. 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
what’s really going on is we’re abstracting  as youall know, radios don’t work like links
Every packet is broadcast
Reception is probabilistic

5. ExOR: Exploiting Probabilistic Broadcast
packet
packet
packet
packet A B
src
dst
packet
packet
packet
packet
packet C
say there’s an opportunity here, take advantage of bcast. spell it out: closest node should reduce the number of tx to get to dest. challenge:: key failure is that two people should not forward. make sure only one guy forwards
Decide who forwards after reception
closest receiver to dst
Challenge: agree efficiently and avoid duplicate transmissions

6. Outline Introduction Why ExOR might increase throughput ExOR protocol
Measurements
Related Work
let’s assume we’re worked out the technical details (defer to design). let’s talk about why and how much of an improvement to expect.

7. Why ExOR Might Increase Throughput (1)
Probabilistic Routing
src N1 N2 N3 N4 N5
dst
75%
50%
25%
new slide earlier, assume figured out design. explore why exor might improve throughput/develop a feel title -> why exor might beat trad routing.
inverse prop to #trans, up to 4 hops
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

8. Why ExOR Might Increase Throughput (2)
Multi-path Diversity N1
25%
100% N2
25%
100%
src
dst
25%
100% N3
100%
25% N4
say this is a contrived example
Traditional routing: 1/ = 5 tx
ExOR: 1/(1 – (1 – 0.25)4) + 1 = 2.5 transmissions
Assumes independent losses

9. ExOR Uses Links in Parallel
possible question – why are there only 7 forwarders.(just say we thin out...)
Traditional Routing
3 forwarders
4 links
ExOR
7 forwarders
18 links

10. Outline Introduction Why ExOR might increase throughput ExOR protocol
Measurements
Related Work

11. Node Agreement  Priority Ordering
LIST: 4321
LIST: 4321
LIST: 4321 N2 N4
src
dst N1 N3
LIST: 4321
LIST: 4321
LIST: 4321
Who is next hop?
nodes “closest” to the destination send first
To avoid collisions, one node sends at a time, ordered from higher priority to lower priority
CLOSEST: Sort by ETX metric to dst
Nodes periodically flood ETX “link state” measurements
Path ETX is weighted shortest path (Dijkstra’s algorithm)
Source sorts, includes a priority list of forwarder in ExOR header
source calculates path etx for each node to dest, talk about dijkstra, sort by lowest etx

12. 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: 100
tx:  9
tx:
 24
src
dst N1 N3
tx:  8
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 90% of the whole batch
Switch to traditional routing
Cannot achieved amortized cost
add circle for source, then some more circles showing next iteration (no rx/tx numbers). say at the end, packets go through multiple iteration. add source, add n4.

13. Reliable Summaries Batch Map Cumulative: what all previous nodes rx’d
tx: {2, 4, , 98}
summary: {1,2,6, , 98, 99}
Fragment N2 N4
src
dst N1 N3
tx: {1, 6, , 96, 99}
Explore path diversity
summary: {1, 6, , 96, 99}
Batch Map
Repeat summaries in every data packet
Cumulative: what all previous nodes rx’d
Avoid duplicated retransmission
This is a gossip mechanism for summaries
just say we incude a summary in every packet
repeated
cumulative
simplify: every node is listening, include list to make it more robust

14. Packet Scheduling
Node transmission ordered from high priority to low priority
Who initiates?
Dst sends 10 empty packets with batch maps
In absence of information , assume each higher priority node transmits at least 5 packets
How to tell the end of fragment transmission
Last packet in current fragment
Timeout
Estimate sender’s time to completion
Sending rate of current sender & remaining packets

15. Scheduling Example

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

17. Using ExOR with TCP
Web Server
Client PC
TCP
ExOR Batches (not TCP)
Node
Gateway
Proxy
Web
Proxy
ExOR
don’t say we will, say we do. Batching interacts badly with tcp. Internet cloud. NOT using TCP in the middle – spell it out
Batching requires more packets than typical TCP window

18. Outline Introduction Why ExOR might increase throughput ExOR protocol
Measurements
Related Work

19. ExOR Evaluation Does ExOR increase throughput?
When/why does it work well?

20. Evaluation Details 65 Node pairs 1.0MByte file transfer
1 kilometer
65 Node pairs
1.0MByte file transfer
1 Mbit/s bit rate
1 KByte packets
Traditional Routing
ExOR
unicast with link-level retransmissions
Hop-by-hop batching
UDP, sending as MAC allows
broadcasts
100 packet batch size
higher throughput implies less time spent on channel

21. ExOR: 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

22. 25 Highest throughput pairs
3 Traditional Hops
2.3x
2 Traditional Hops
1.7x
1 Traditional Hop
1.14x
1000
ExOR
800
Traditional Routing
600
Throughput (Kbits/sec)
400
for the two hop, say we can have more intermediate hops like ex 2 or make it all the way
200
Node Pair
- Gossiped ACKs prevents incorrect retransmission
- More available intermediate forwarders

23. 25 Lowest throughput pairs
1000
ExOR
4 Traditional Hops
3.3x
800
Traditional Routing
600
Throughput (Kbits/sec)
400
200
etx was forced to use asymmetric links. robust batch maps.
Node Pair
Longer Routes
- Utilize asymmetric link by gossiped batch map from different path

24. 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
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
- Utilize Long & Lossy Link

25. Future Work Choosing the best 802.11 bit-rate
Cooperation between simultaneous flows
Coding/combining

26. Summary ExOR achieves 2x throughput improvement
ExOR implemented on Roofnet
Exploits radio properties, instead of hiding them
Discussion
Memory requirement for packet buffering
Jitters
Instantaneous link quality N2
135
dst N1
Dst needs 3, but N2 has 3  Don’t send
Need 3 ?
1346