xors in the air: practical wireless network coding
DESCRIPTION
XORs in the air: Practical Wireless Network Coding. Sachin Katti , Hariharan Rahul , Wenjun Hu , Dina Katabi , Muriel Medard , Jon Crowcroft SIGCOMM ‘06. Presented by Thangam Seenivasan. Problem. Increase the throughput of dense wireless networks. Network Coding. Current Approach. - PowerPoint PPT PresentationTRANSCRIPT
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XORs in the air: Practical Wireless Network Coding
Sachin Katti, Hariharan Rahul, Wenjun Hu, Dina Katabi, Muriel Medard, Jon Crowcroft
SIGCOMM ‘06
Presented byThangam Seenivasan
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Problem
Increase the throughput of dense wireless networks
Network Coding
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Current Approach
Alice BobRelay
A B
A
B
A
B
Requires 4 transmission
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COPE Approach
Alice BobRelay
A B
AB
Requires 3 transmission
A XOR B
Increased throughput
A XOR B
XOR
A XOR B
XOR
B
=A
=
A XOR B A XOR B
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COPE Approach• Exploits shared nature of wireless medium– Every node snoops on all packets– A node stores all heard packets for a limited time
• Tell neighbors which packets it has heard• Perform opportunistic coding– XOR multiple packets and transmit them as single
packet• Decode the encoded packet using stored
packets
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Scenario
S1
D1
S2
D2
R
A B
A
A B
B
A+B
A+B A+BB A
Requires 3 transmission
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Outline
• Design • Cope Gains• Making it work• Implementation details• Experimental results
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Overview
• Opportunistic listening• Opportunistic coding• Learning neighbor state
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Opportunistic listening
• Exploit broadcast nature of wireless– Set nodes in promiscuous mode– Opportunities to overhear packets
• Store the overheard packets– Limited time period (T = 0.5s)
• Broadcast reception reports to tell neighbors which packets it has stored– Annotate with data packets– If no data packets, send reception reports periodically
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Opportunistic coding
What packets to code together to maximize throughput?
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Opportunistic coding
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Opportunistic coding
P1 + P2
Bad Coding – C can decode but A can’t
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Opportunistic coding
P1 + P3
Better Coding – Both A and C can decode
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Opportunistic coding
P1 + P3 + P4
Best Coding – Nodes A, C, D can decode
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Opportunistic coding
• Maximize the number of native packets delivered in a single transmission
• While ensuring that each intended next hop has enough information to decode its native packet
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Opportunistic coding
To transmit n packets: p1, …., pn
To n next hops: r1, …., rn
A node can XOR the n packets together only if each next hop ri has all n-1 packets pj for j!=i
Choose the largest n that satisfies the above rule
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Learning Neighbor State
How does a node know what packets its neighbors have?
• Send reception reports• During congestion, reports may get lost in
collisions or may arrive late
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Learning Neighbor State
• Wireless routing protocols compute delivery probability between every pair of nodes and broadcast them– E.g.: ETX
• Using these weights, – Estimate the probability that a particular neighbor
has a packet
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Outline
• Design • Cope Gains• Making it work• Implementation details• Experimental results
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COPE Gains
• Coding Gain• Coding + MAC Gain
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Coding Gain
Number of transmissions required by non-coding approach
Minimum number of transmissions used by COPE
Coding Gain =
Alice & Bob experiment – Coding gain = 4/3 = 1.33
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Coding Gain
Coding gain = 4/3 = 1.33 Coding gain = 8/5 = 1.6
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Coding + MAC GainAlice BobRouter
A
B
A
B
• MAC divides the bandwidth equally between the 3 contending nodes
• The router needs to transmit twice as many packets• Hence router is a bottleneck– Half the packets are dropped as routers queue
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Coding + MAC GainAlice BobRouter
A
B
• COPE – XOR pairs of packets– router drains packets twice as fast
A + B
Coding + MAC gain = 2
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Coding + MAC Gain
• For topologies with single bottleneckDraining rate with COPE
Draining rate without COPECoding + MAC Gain =
Coding + MAC gain = 2 Coding + MAC gain = 4
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Coding + MAC Gain
• In the presence of opportunistic listening, COPE’s maximum Coding + MAC gain is unbounded.
N -> ∞
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Outline
• Design • Cope Gains• Making it work• Implementation details• Experimental results
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Making it work
• Packet Coding Algorithm• Packet Decoding• Pseudo-broadcast• Hop-by-hop ACKs and Retransmissions• Preventing TCP packet reordering
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Packet Coding Algorithm
• Never delaying packets– Does not wait for additional codable packets to arrive
• Preference to XOR packets of similar lengths– Pad zeros if different lengths
• Maintain two virtual queues per neighbor– One for small, one for large packets
• Dequeue the packet at the head of the FIFO– Look only at the head of the virtual queues
• Each neighbor has a high probability of decoding the packet – Threshold probability
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Packet Coding Algorithm
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Packet Decoding
• Each node maintains a Packet Pool– Packets it received or sent out
• Packets are stored in a hash table keyed on packet id
• Encoded packet with n packets– XOR with n – 1 packets from packet pool
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Pseudo-broadcast
• Broadcast– No ACKs– No retransmissions– Poor reliability and lack of back-off
• Unicast– ACKed as soon as received– Sender back-off exponentially if no ACKs– Retransmissions– More Reliable
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Pseudo-broadcast
• Pseudo-broadcast– Unicast packet to one of its recipients– That node ACKs and hence the transmission is
reliable– Since others listen in promiscuous mode they
receive the packet as well– An XOR header is added after the link-layer header
listing all next hops• Each node checks the XOR header if it is a recipient and
processes the packet
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Hop-by-hop ACKs and Retransmissions
• Encoded packets require all next hops to ack the receipt of the associated native packet– Only one node ACKs (pseudo-broadcast)– There is still a probability of loss to other next hops– Hence, each node ACKs the reception of native packet– If not-acked, retransmitted, potentially encoded with other
packets– Overhead - highly inefficient
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Hop-by-hop ACKs and Retransmissions
• Asynchronous ACKs and Retransmissions– Cumulatively ACK every Ta seconds– If a packet is not ACKed in Ta seconds,
retransmitted – Piggy-back ACKs in COPE header of data packets– If no data packets, send periodic control packets
(same packets as reception reports)
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Preventing TCP Packet Reordering
• Asynchronous ACKs can cause packet reordering– TCP can take this as a sign of congestion
• Ordering agent– Ensures TCP packets are delivered in order– Maintains packet buffer
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Outline
• Design • Cope Gains• Making it work• Implementation details• Experimental results
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Packet Format
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Control flow - Sender
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Control flow - Receiver
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Outline
• Design • Cope Gains• Making it work• Implementation details• Experimental results
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Testbed• 20 nodes
– Path between nodes are 1 to 6 hops in length– 802.11a with a bit-rate of 6Mb/s
• Software– Linux and click toolkit– User daemon and exposes a new interface– Applications use this interface
• No modification to application is necessary
• Traffic model– udpgen to generate UDP traffic– ttcp to generate TCP traffic– Poisson arrivals, Pareto file size distribution
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Metrics
• Network throughput– Total end-to-end throughput (sum of throughput
of all flows in a network)• Throughput gain– The ratio of measured throughput with and
without COPE– Calculate from two consecutive experiments, with
coding turned on and off
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Long-lived TCP flows
Close to 1.33 Close to 1.33 Close to 1.6
• Close to coding gain– TCP backs-off due to congestion control– To match the draining rate at the bottleneck
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Long-lived UDP flows
1.7 1.65 3.5
• Close to Coding + MAC gain– XOR headers add small overhead (5-8%)– The difference is also due to imperfect overhearing
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Ad-hoc network - TCP
• TCP flows– Arrive according to Poisson process– Pick sender and receiver randomly– Transfer files (size - Pareto distribution)
• Does not show any significant improvement– TCP’s reaction to collision-related losses– Hidden terminals
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Ad-hoc network - TCP
• Even with 15 MAC retries, 14% loss– Due to hidden terminals
• Bottleneck never see enough traffic to make use of coding– Few coding opportunities
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TCP with no hidden terminals
38% improvement in TCP goodput
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Ad-hoc network - UDP
3-4x improvement in throughput
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Ad-hoc network - UDP
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Ad-hoc network - UDP
On an average 3 packet are coded together
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Mesh network
• COPE throughput gain relies on coding opportunities– Depends on diversity of packets in the queue of the
bottleneck node
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Fairness
More fair – more opportunities to code
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Conclusion
• Network coding to improve the throughput of wireless networks
• COPE -Implementation of first system architecture for wireless network coding
• COPE improves the UDP throughput by 3-4x• 5% to 70% throughput improvement in mesh
networks depending on downlink-uplink ratio
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Thank You Questions?