Opportunistic Routing in MultiHop Wireless Networks

1
ExOR Opportunistic Multi-Hop Routing for
Wireless Networks
Sanjit Biswas and Robert Morris M.I.T. Computer
Science and Artificial Intelligence Laboratory
Presented by Deepak Bastakoty
With slides from Sanjit Biswas, Robert Morris,
(MIT) Saurabh Gupta (WPI) Yao Zhao (Northwestern)
2
Multi-Hop Wireless Networks
2km
Gateway
Gateways
2km

• Dense 802.11b-based mesh, all sorts of loss rates
• Goal is efficiency and high-throughput

3
The Traditional View
packet
packet
packet
A
B
src
dst
packet
packet
C

• Identify a route, forward over links
• Use link level retransmissions

4
How Radios Actually Work
A
B
src
dst
1
2
3
4
5
6
1
2
3
6
3
5
1
4
2
3
4
5
6
1
2
4
5
6
C

• Every packet is broadcast

No such thing as a link
5
ExOR Exploiting the Insight
A
B
src
dst
packet
packet
packet
packet
packet
C
packet
packet
packet
packet

• Figure out which nodes rxd broadcast
• Node closest to destination forwards

6
ExOR Exploiting the Insight
packet
packet
packet
packet
A
B
src
dst
packet
packet
packet
packet
packet
C

• Figure out which nodes rxd broadcast
• Node closest to destination forwards

7
ExORs Assumptions

• Many receivers hear every broadcast
• Gradual distance-vs-reception tradeoff
• Receiver losses are uncorrelated

A
B
src
dst
C
8
1. Multiple Receivers per Transmission

• Broadcast tests on rooftop network
• Source sends packets at max rate
• Receivers record delivery ratios
• Omni-directional antennas
• Multiple nodes in radio range

100
1km
75
50
25
0
S
9
2. Gradual Distance vs. Reception Tradeoff
Same Source
Delivery Ratio
Distance (meters)

• Wide spread of ranges, delivery ratios
• Transmissions may get lucky and travel long
  distances

10
3. Receiver Losses are Uncorrelated
Example Broadcast trace
Receiver 1 (38)
Receiver 2 (40)
Receiver 3 (74)
Receiver 4 (12)

• Two 50 links dont lose the same 50 of packets
• Losses not due to common source of interference

11
Extremely Opportunistic Routing (ExOR) Design
Goals

• Ensure only one receiver forwards the packet
• The receiver closest to the destination should
  forward
• Lost agreement messages may be common
• Lets not get eaten alive by overheads

12
How ExOR might provide more throughput
N5
N1
N3
N7
N6
N2
N4
N8
S
D
Traditional Path

• Traditional routing must compromise between hops
  to choose ones that are long enough to make good
  progress but short enough for low loss rate
• With ExOR each transmission may have more
  independent chances of being received and
  forwarded
• It takes advantage of transmissions that reach
  unexpectedly far, or fall unexpectedly short

13
How ExOR might provide more throughput (contd..)
N1
25
100
N2
25
100
src
dst
100
25
N3
100
25
N4

• Traditional routing 1/0.25 1 5 transmissions
• ExOR 1/(1 (1 0.25)4) 1 2.5 transmissions
• Assumes independent losses

14
ExOR Protocol

• How often should ExOR run?
• Per packet is expensive
• Use batches
• Who should participate in the forwarding?
• Too many participants cause large overhead
• When should each participant forward?
• Avoid simultaneous transmission
• What should each participant forward?
• Avoid duplicate transmission
• How and When does the process complete?
• Identify the convergence of the algorithm

Jump Ahead
15
Who should participate?

• The source chooses the participants (forwarder
  list) using ETX-like metric
• Only considers forward delivery rate
• The source runs a simulation and selects only the
  nodes which transmit at least 10 of the total
  transmission in a batch
• A background process collects ETX information via
  periodic link-state flooding

16
When should each participant forward?

• Forwarders are prioritized by ETX-like metric to
  the destination
• Receiving nodes buffer successfully received
  packets till the end of the batch
• The highest priority forwarder transmits from its
  buffer when the batch ends
• These transmissions are called the nodes
  fragment of the batch
• The remaining forwarders transmit in prioritized
  order
• Question How does each forwarder know it is its
  turn to transmit
• Assume other higher priority nodes send for five
  packet durations if not hearing anything from them

17
What should each participant forward?

• Packets it receives yet not received by higher
  priority forwarders
• Each packet includes a copy of the senders batch
  map, containing the senders best guess of the
  highest priority node to have received each
  packet in the batch
• Question How does a node know the set of packets
  received by higher priority nodes?
• Using batch map

18
How and When does the process complete?

• If a nodes batch map indicates that over 90 of
  the batch has been received by higher priority
  nodes, the node sends nothing when its turn comes
• When ultimate destinations turn comes to send,
  it transmits 10 packets including only its batch
  map and no data
• Question How is the remaining 10 data
  delivered?
• Using traditional routing

19
Who Received the Packet?
Standard unicast 802.11 frame with ACK
payload
ACK
src
dest
src
dest
ExOR frame with slotted ACKs
payload
ACK1
cand1
cand2
cand3
src
ACK2
ACK3
src
cand1
cand2
cand3

• Slotting prevents collisions (802.11 ACKs are
  synchronous)
• Only 2 overhead per candidate, assuming 1500
  byte frames

20
Slotted ACK Example
A
B
C
D

• Packet to be forwarded by Node C
• But if ACKs are lost, causes confusion

21
Agreeing on the Best Candidate
A
B
C
D
X
X

• A Sends frame with (D, C, B) as candidate set

D Broadcasts ACK D in first slot (not rxd
by C, A)
C Broadcasts ACK C in second slot (not rxd
by D)
B Broadcasts ACK D in third slot
Node D is now responsible for forwarding the
packet
22
ExOR Packet Format

• HdrLen PayloadLen indicate size of ExOR header
  and payload respectively
• PktNum is current packets offset in the batch,
  corresponding to the current batch-map entry
• FragSz is size of currently sending nodes
  fragment (in packets)
• FragNum is current packets offset within the
  fragment
• FwdListSise is is number of forwarders in list
• ForwarderNum is current senders offset within
  the list
• Forwarder List is copy of senders local
  forwarder list
• Batch Map is copy of sending nodes batch map,
  where each entry is an index into Forwarder List

23
Transmission Timeline for an ExOR transfer
N24 not able to listen to N5.
N8 does not send
N17 might have missed some batch-maps
24
Preliminary Concept Evaluation

• Strengths
• ExOR is nimble
• Efficient in total number of packet transmissions
• Weaknesses
• Requires (partial) link-state graph
• Candidate selection is tricky
• Requires changes to MAC

25
65 Roofnet node pairs
1 kilometer
26
ExOR 2x Improvement in throughput
1.0
0.8
0.6
Cumulative Fraction of Node Pairs
0.4
0.2
ExOR
Traditional
0
0
200
400
600
800
Throughput (Kbits/sec)
Figure 8 The distribution of throughputs of ExOR
and traditional routing between the 65 node
pairs. The plots shows the median throughput
achieved for each pair over nine experimental
runs.
Median throughputs 240 Kbits/sec for ExOR,
121 Kbits/sec for Traditional
27
25 Highest throughput pairs
1 Traditional Hop 1.14x
2 Traditional Hops 1.7x
3 Traditional Hops 2.3x
1000
ExOR
Traditional Routing
800
600
Throughput (Kbits/sec)
400
200
0
Node Pair
Figure 9 The 25 highest throughput pairs, sorted
by traditional routing throughput. The bars show
each pair's median throughput, and the error bars
show the lowest and highest of the nine
experiments.

• For single hop pairs ExOR provides the advantage
  of lower probability of source resending packets,
  as theres higher probability of source receiving
  the destinations 10 batch-map packets

28
25 Lowest throughput pairs
1000
ExOR
4 Traditional Hops 3.3x
Traditional Routing
800
600
Throughput (Kbits/sec)
400
200
0
Node Pair
Longer Routes
Figure 10 The 25 lowest throughput pairs. The
bars show each pair's median throughput, and the
error bars show the lowest and the highest of the
nine experiments. ExOR outperforms traditional
routing by a factor of two or more.

• As number of node pairs increases along a route,
  the likelihood of increased choice of forwarding
  nodes and multiple ways to gossip back
  batch-maps, increases
• With greater routing length ExOR is able to take
  advantage of asymmetric links also

29
Retransmissions affected by selection of hops
Figure 11 The number of transmissions made by
each node during a 1000-packet transfer from N5
to N24. The X axis indicates the sender's ETX
metric to N24. The Y axis indicates the number of
packet transmissions that node performs. Bars
higher than 1000 indicate nodes that had to
re-send packets due to losses.
30
ExOR moves packets farther
Figure 12 Distance traveled towards N24 in ETX
space by each transmission. The X axis indicates
the dierence in ETX metric between the sending
and receiving nodes the receiver is the next hop
for traditional routing, and the highest-priority
receiving node for ExOR. The Y axis indicates the
number of transmissions that travel the
corresponding distance. Packets with zero
progress are not received by the next hop (for
traditional routing) or by any higher-priority
node (for ExOR).
31
ExOR moves packets farther
0.6
ExOR
Traditional Routing
0.2
Fraction of Transmissions
0.1
0
0
100
200
300
400
500
600
700
800
900
1000
Distance (meters)

• Delivery Probability decreases with distance
• ExOR average 422 meters/transmission
• Traditional Routing average 205 meters/tx

32
ExOR uses links in parallel
Traditional Routing 3 forwarders 4 links
ExOR 7 forwarders 18 links
33
Batch Size

• ExOr header grows with the batch size
• Large batches work well for low-throughput pairs
  due to redundant batch map transmissions
• Small batches work well for high throughput pairs
  due to lower header overhead

34
Critical Analysis

• Static
• No mobility
• Small Scale
• Tens of nodes
• Dense network
• - Maybe Only Rooftop Networks
• File downloading application
• No voice, maybe not web (No reliable guarantee)
• No Cross Traffic

35
Static

• Knowing the whole topology
• In a mobile network, this is expensive
• EXT is costly
• Measure link states of all possible links
• Route change
• During a batch, route may change

36
Small Scale

• Knowing the whole topology
• In a mobile network, this is expensive
• EXT is costly
• Measure link states of all possible links
• Large overhead in ExOR packet header
• All the forwarders are included in ExOR header
• Long vain waiting of forwarding timer
• The larger the network, the longer the average
  distance between S and D, the more forwarders in
  the list
• Traditional header (2448 -gt 8 if AODV)
• ExOR header (44114 for 38-node network)

37
Dense Networks
A
C
S
E
X
B
D
38
Dense Networks
39
More Critical AnalysisYao Zhao (Northwestern)

• No TCP and hence proxy
• Voice
• Jitter
• Web service
• Is batch good?
• May introduce large delay
• Large file download
• Best for ExOR

40
Cross TrafficYao Zhao (Northwestern)

• Forwarding timer
• Give higher-priority nodes enough time to send?
• Assume 5 packets sent if a node cannot hear
  another node with higher priority hard to
  justify heuristic. Also, forwarders could be
  consistently mutually inaccessible
• 802.11 use CSMA/CA, competition based MAC
• If there is cross traffic, hard to estimate the
  transmission time of other nodes

41
Unfair Comparison ?Yao Zhao (Northwestern)

• Bad Traditional routing (DSR)
• Dont think about link state changing
• Long packet header
• Send the entire file to the next node before the
  next node starts sending
• Bad MAC Selection
• Retransmit packet if ACK is lost
• Why not packet train?
• A Paper in 2005 compared to some works before
  1999 ?

42
Questions?
43
Acknowledgements

• Many sketches, animated-diagrams, as well as some
  text have been sourced from the following
  materials-
• Course material on Net Centric Systems taught
  at TECHNISCHE UNIVERSITÄT DARMSTADT
• Presentation on A High Throughput Route-Metric
  for Multi-Hop Wireless Routing by Eric Rozner of
  University of Texas, Austin
• Presentation on ExOR Opportunistic Multi-Hop
  Routing for Wireless Networks, by Sanjit Biswas
  and Robert Morris at Siggcomm
• ExOR Opportunistic Multi-Hop Routing for
  Wireless Networks - Sanjit Biswas and Robert
  Morris
• Presentation on ExOR Opportunistic Multi-Hop
  Routing for Wireless Networks, by Avijit of
  University of California, Santa Barbara
• Presentation on ExOR Opportunistic Multi-Hop
  Routing for Wireless Networks, by Yu Sun of
  University of Texas, Austin
• Presentation on ExOR Opportunistic Multi-Hop
  Routing for Wireless Networks, by Gaurav Gupta,
  University of Southern California
• Presentation on ExOR Opportunistic Multi-Hop
  Routing for Wireless Networks, by Ao-Jan Su,
  Northwestern University