1. Network Coding and Reliable Communications Group DAWN PI meeting – October 2009 Network coding with unreliable, unknown bandwidths Muriel Medard EECS RLE MIT Joint work with Szymon Jakubczak, Daniel Lucani, Jay-Kumar Sundararajan, Joao Baros (University of Porto), Frank Fitzek (University of Aalborg), Michael Mitzenmacher (Harvard University), Milica Stojanovic (Northeastern),

2. Network Coding and Reliable Communications Group DAWN PI meeting – October 2009 Overview Network coding changes the way that we can consider data manipulation and dissemination in networks One important aspect of this is how to characterize the usefulness of nodes’ received information consisting of coded packets We examine two main areas: –File dissemination among nodes in wireless multihop systems –Using network coding with TCP to enhance throughput and reliability

3. Network Coding and Reliable Communications Group DAWN PI meeting – October 2009 Application: Network coding for file dissemination –Data dissemination All nodes require all information Nodes start with some data: no constraint –Wireless nodes Half-duplex: Node can transmit and receive, but not at the same time Broadcast advantage: one tx can benefit several nodes Previous work: –Gossip algorithms, flooding, broadcasting # data packets ≤ # nodes Data is not concentrated at one node No losses –Practical schemes for network coding, e.g. priority to node with more information (progressive base station)

4. Network Coding and Reliable Communications Group DAWN PI meeting – October 2009 Mobile devices are lined up with different distances (link quality to the base station) Packet erasures All devices want to receive all information What is the right strategy? 100%75%50%25% Dissemination of a file

5. Network Coding and Reliable Communications Group DAWN PI meeting – October 2009 Greedy algorithm 100%75%50%25% coding horizon for device 1 forward disseminationbackward healing coding horizon for device i device idevice j

6. Network Coding and Reliable Communications Group DAWN PI meeting – October 2009 Toy example Progressive Base Station: Greater Impact (Vanilla): M Data Packets Slots 0 0 M M/2 3M/2 M 2M5M/2 3M/2 2M

7. Network Coding and Reliable Communications Group DAWN PI meeting – October 2009 Dissemination time gains: no losses 20 nodes 20 packets Overhearing of N = 2

8. Network Coding and Reliable Communications Group DAWN PI meeting – October 2009 Dissemination time gains: losses Fixed number of nodes Overhearing reduces gain, but reduces completion time

9. Network Coding and Reliable Communications Group DAWN PI meeting – October 2009 TCP using network coding Random linear network coding masks link losses from TCP in order to prevent unnecessary back-off Novel ACK design that accounts for mixing (coding) of packets with each other –Allows ACK of every innovative linear combination, even if it does not reveal a packet immediately Network coding layer between TCP and IP

10. Network Coding and Reliable Communications Group DAWN PI meeting – October 2009 The specifics Coding layer buffers packets given by TCP For every packet coming from TCP, coding layer transmits r (>1) random linear combinations of buffered packets to IP Acknowledgment: ACK a packet upon seeing it (even before it is decoded) Can do this at intermediate nodes as well in a daisy chain (tandem) network Redundanc y factor

11. Network Coding and Reliable Communications Group DAWN PI meeting – October 2009 The specifics

12. Network Coding and Reliable Communications Group DAWN PI meeting – October 2009 Experimental results (Reno)

13. Network Coding and Reliable Communications Group DAWN PI meeting – October 2009 Experimental results (Reno) Goodput versus redundancy factor for a 10% loss rate

14. Network Coding and Reliable Communications Group DAWN PI meeting – October 2009 Window size issues

15. Network Coding and Reliable Communications Group DAWN PI meeting – October 2009 Window size Note that a coding window size of W = 1 corresponds to a repetition code that simply transmits every packet 1.06 times on average. In comparison, A simple sliding window code with W = 2 brings a big gain in throughput by making the added redundancy more useful Going beyond 2 reduces the goodput because a large value of W can mislead TCP into believing that the capacity is larger than it really is, which leads to timeouts We find that the best value of W for our setup is usually 2 for a loss rate up to around 5 %, and is 3 for higher loss rates up to 25% Besides the loss rate, the value of W could also depend on other factors such as the round-trip time of the path.

16. Network Coding and Reliable Communications Group DAWN PI meeting – October 2009 Conclusions We have shown that network coding can be used to manage content in networks for file distribution and for flow transmission The main thrust is to maintain a representation of degrees of freedom, without necessarily a detailed description of the space available at a node The use of coding allows us to reduce delay and increase throughput if we design the system carefully