Presentation on theme: "A Digital Fountain Approach to Reliable Distribution of Bulk Data"— Presentation transcript:
1A Digital Fountain Approach to Reliable Distribution of Bulk Data John Byers, ICSIMichael Luby, ICSIMichael Mitzenmacher, Compaq SRCAshu Rege, ICSI
2Application: Software Distribution New release of widely used software.Hundreds of thousands of clients or more.Bulk data: tens or hundreds of MBHeterogeneous clients:Modem users: hoursWell-connected users: minutes
3Primary Objectives Scale to vast numbers of clients No ARQs or NACKsMinimize use of network bandwidthMinimize overhead at receivers:Computation timeUseless packetsCompatibilityNetworks: Internet, satellite, wirelessScheduling policies, i.e. congestion control
4Impediments Packet loss Receiver heterogeneity wired networks: congestionsatellite networks, mobile receiversReceiver heterogeneitypacket loss ratesend-to-end throughputReceiver access patternsasynchronous arrivals and departuresoverlapping access intervals
5Digital Fountain k Source Instantaneous Encoding Stream Transmission k ReceivedInstantaneousCan recover filefrom any set ofk encoding packets.kMessage
7Is FEC Inherently Bad? Faulty Reasoning But… FEC adds redundancy Redundancy increases congestion and lossesMore losses necessitate more transmissionsFEC consumes more overall bandwidthBut…Each and every packet can be useful to all clientsEach client consumes minimum bandwidth possibleFEC consumes less overall bandwidth by compressing bandwidth across clients
8DF Solution FeaturesUsers can initiate the download at their discretion.Users can continue download seamlessly after temporary interruption.Tolerates moderate packet loss.Low server load - simple protocol.Does scale well.Low network load.
9Approximating a Digital Fountain kSourceEncoding TimeEncodingStream(1 + c) kReceivedDecoding TimekMessage
10Approximating a DF: Performance Measures Time Overhead:Time to decode (or encode) as a function of k.Decoding Inefficiency:packets needed to decodek
11Work on Erasure Codes Standard Reed-Solomon Codes Dense systems of linear equations.Poor time overhead (quadratic in k)Optimal decoding inefficiency of 1Tornado Codes [LMSSS ‘97]Sparse systems of equations.Fast encoding and decoding (linear in k)Suboptimal decoding inefficiency
19Digital Fountain Prototype Built on top of IP Multicast.Tolerating heterogeneity:Layered multicastCongestion control [VRC ‘98]Experimental results over MBONE.
20Research Directions Other applications for digital fountains Dispersity routingAccessing data from multiple mirror sites in parallelImproving the codesImplementation and deploymentScale to large number of clientsNetwork interactions