UFlood: High-Throughput Wireless Flooding

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UFlood High-Throughput Wireless Flooding
Jayashree Subramanian Collaborators Robert
Morris, Ramakrishna Gummadi, and Hari Balakrishnan
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Goal of this work

• To design a flooding protocol for wireless
  multi-hop networks
• Application Real-time video distribution
• What is a good flooding protocol?
• Use least transmissions
• Provide high-throughput for the nodes

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Challenge in Wireless Flooding

• Every transmission is broadcast (Opportunistic
  Receptions!)
• Reception is probabilistic

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4
A
B
Delivery probability from Src to B
0.1
src
D
1
1
1
2
1
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2
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2
3
C
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6
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Challenge in Wireless Flooding contd

• Challenge
• Who should transmit next?
• What packet to transmit?
• UFloods claim Select best sender to minimize
  total transmissions to complete flooding

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Contribution of this work

• UFlood Choosing best sender for every
  transmission maximizes throughput
• UFlood performance
• Achieves 2x higher throughput than controlled
  flooding
• Performs close to the benchmark - ExOR unicast
  routing (multihop transfer to a single receiver)

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Outline of this talk

• Existing Solutions
• Key Idea of UFlood
• Design of UFlood protocol
• Evaluation

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Related Work

• Flooding in routing
• Controlled flooding (AODV, DSR)
• Does not maximize throughput
• Tree-based flooding
• MCDS, LESS
• Does not consider opportunism
• Gossip-based flooding

1. Tree-based flooding (static decision)

0.1
Wasted transmission!
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Related Work contd

• Gossip-based flooding (dynamic
  decision)
• Trickle, Deluge
• Does not choose best sender

Bad sender choice means more transmissions!
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Outline of this talk

• Existing Solutions
• Key Idea of UFlood
• Design of UFlood protocol
• Evaluation

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Key Idea
Select the best sender - to maximize Useful
Receptions
Select the best sender - to maximize throughput
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A
B
0.9
Packet availability
Delivery probability
0.1
src
D
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C
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Calculating Useful Receptions
U(B,1)0
U(A,4) 0.90.40.61.8
1
4
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1
A
B
0.9
0.4
src
D
0.6
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1
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1
C
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To Flood a Single Packet using UFlood
U(S)1.7
U(S)0.7
S
0.5
0.5
A
U(A)1.5
B
1
0.2
0.3
U(D)0.8
D
0.5
C
To flood multiple packets calculate utility for
every packet!s
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UFlood is a Local Heuristic

• Difficulty Knowing the packet availability at
  all nodes
• Solution Local heuristic- Every node knows only
  about its neighbors (nodes whose packets it can
  hear!)
• Good news Possibility of spatial reuse!

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Outline of this talk

• Existing Solutions
• Key Idea of UFlood
• Design of protocol
• Evaluation

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Design of UFlood

• Information required
• Node states - packets available with the
  neighbors
• Delivery probabilities of all node pairs in the
  network

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Knowing Node States

• Node states
• Ni- number of neighbors of i
• P packets flooded
• node-state matrix NixP
• Method
• Maintain local version
• Gossip packet availability using periodic status
  packets

Packet
3
2
1
3
2
1
Node
0
1
1
1
1
1
1
0
1
0
2
1
0
2
0
0
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0
3
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Computing Delivery Probabilities

• Delivery probabilities
• For all N nodes in the network
• Delivery prob matrix NxN
• Method offline experiment
• Each node broadcasts continuous probes and rest
  of the nodes compute

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Computing Packet Utility
Node states
Delivery probabilities
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Pseudo code of UFlood

• Source Node floods all packets
• All nodes periodically broadcast status packet
• On reception of a new data or status packet
• Update node-state matrix
• Calculate utility
• Transmit in burst all packets whose utility is
  greater than neighbors utility
• CSMA handles contention (Listen then send or back
  off)

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Batching in UFlood

• The packets are sent in batches
• To reduce overhead
• To limit the size of the status packet
• Current design considers single batch!

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Outline of this Talk

• Existing Solutions
• Key Idea of UFlood
• Design of UFlood protocol
• Evaluation

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20-Node Indoor Test-bed
200 feet
250 feet
Source Node
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Implementation

• Meraki mini, 802.11b/g
• 2dbi Omni-directional antenna
• Transmit power 60mW
• Bit rate 24Mbps
• CLICK software router toolkit
• Carrier Sense on

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Performance Comparison

• Method Flood a single batch of 5000-1500B packet
• Comparison
• UFlood Vs. Controlled Flooding
• UFlood Vs. Unicast routing

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UFlood Vs. Controlled Flooding

• Used in routing protocols like AODV and DSR
• Method
• Source broadcasts all packet
• Every node rebroadcasts only once
• Why we used?
• Aim to quickly send the route information

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Throughput of UFlood 2x Throughput of
Controlled Flooding
No Choice of Sender!
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UFlood Vs. Estimated Unicast

• Why unicast?
• Multihop transfer to
• one receiver Vs many receivers
• Method
• Setup independent unicast sessions to send a
  batch of packets from source (node 4) to each
  node

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ExOR
packet
packet
packet
packet
A
B
src
dst
packet
packet
packet
packet
packet
C

• Decide who forwards after reception
• Goal only closest receiver should forward

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Throughput of UFlood Throughput of Estimated
ExOR
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Why does UFlood Perform good?
Second best node transmits!
UFlood is a local heuristic Occasional errors!
Best node transmits!
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Future Work

• Implement network-coding, bit-rate adaptation,
  and batching
• UFlood vs. existing high-throughput flooding
  protocols

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Conclusion

• UFloods Key Idea Choosing best sender for
  every transmission maximizes throughput
• UFloods Performance
• Achieves 2x higher throughput than controlled
  flooding
• Performs close to the benchmark - ExOR unicast
  routing