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A. Patwardhan, CSE 581

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Digital Fountains

Main Ideas : Distribution of bulk data Reliable multicast, broadcast Ideal digital fountain Erasure codes RMDP Benefits and applicability

CSE 581, Winter 2002

Instructor : Wu-chang Feng

-Anand Patwardhan

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A. Patwardhan, CSE 581

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Paper group “A Digital Fountain approach to reliable

distribution of bulk data”, J. Byers, M. Luby et al. ( Feb. ’98)

“Accessing multiple mirror sites in parallel: Using Tornado codes to speed up downloads”, J. Byers, M. Luby, M. Mitzenmacher

“RMDP: An FEC-based Reliable Multicast Protocol for Wireless Environments”, L. Rizzio, L. Vicisano (April ’98)

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Reliable distribution of Bulk Data Multicasting with

feedback Reliability : ARQ -

Some solutions use NACK suppression , local recovery – overhead

Scalability – complexity in maintaining group hierarchy

Feedback channel required

Unicasting Reliability : uses ARQ –

Automatic retransmission request

Scalability - Suffers from “Feedback implosion at source”

Efficiency – “repair” packets do not benefit everyone

Requires a feedback channel

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An Ideal “Digital Fountain” A Server serving a universe of clients Source data = k packets is encoded to n

= c.k packets (c>1) Server carousels through a stream of n

packets (uses multicast ) Clients drink their fill Clients quenched by any k subset of the

n packets, then disconnect Clients can “drink” at anytime

(asynchronous)

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Erasure Codes Also known as Forward Error-

Correcting codes (FEC) Most commonly used : Reed-

Solomon erasure codes k = source data packets encoded n = k + l = c.k

c = stretch factor l = redundant packets

Encoding/decoding complexity increases proportional to k*l*(packetsize)

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Tornado Codes

Much simpler than Reed-Solomon Use XOR only Encoding/decoding uses random bipartite graphs n = k+l, but slightly more than k packets have to

be received at the receiver for decoding ( reception inefficiency)

Fast encoding/decoding at the price of reception inefficiency ( usually around 5%)

Encoding/Decoding complexity proportional to (k+l)ln(1/e)*(packetsize)

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Comparison of encoding/decoding times

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Reception overhead

90% clients were done at 0.06For Tornado A

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Comparison of reception efficiency for codes with comparable decoding time

p = probability of loss

Interleaved = data broken into segments and then encodedusing Reed-Solomon codes, k = no of segments

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A. Patwardhan, CSE 581

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Comparison of reception efficiency for codes with increasing filesize

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Simple Mirroring

User has to pick a single site Access intervals often overlap Many to many distribution not

possible

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Parallel download from multiple mirror sites Digital fountain mirrors

Scalable, efficient, reliable, tolerant and on-demand

Client collects packets from multiple senders until “quenched”

“Out-of-step” senders and increased stretch factor (n = c.k) minimize duplicate packets

All available bandwidth utilized to speed up download (concept of “disjoint bottlenecks”)

Effectively “Many-to-many” distribution

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Reception inefficiency, Speedup & stretch

Duplicates decrease Speedup Increases

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RMDP protocol Reliable Multicast data Distribution Protocol Similar to approach of Digital fountains Uses Reed-Solomon, with limited ARQ Authors contend that computational complexity

of Reed-Solomon better than resource expensive Tornado codes in the longer term ( CPUs will improve...)

Optimal values of n,k,l used, claim : expensive but adequate

Feedback suppression, using rules for timeouts

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Reliable multicast using erasure codes

Benefits Reliability with little or no feedback Highly scalable Clients can join asynchronously Ideal for wireless, satellite, cable

transmissions with little or non-existent feedback channel

Performance does not decrease with increase in receivers, due to correlated losses

Resilient to bursty losses

Drawbacks Zero feedback at the

cost of bandwidth, buffers and time

Encoding, decoding overhead

Increased buffers Reception inefficieny Data available only after

a minimum set of distinct packets arrive

Does not consider CC

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Summary Reliability achieved by “carouseling”

packets encoded using erasure codes A single packet from a block is potentially

useful for a large subset of the receivers Both RMDP and the Digital fountain

approach, use multicasting and erasure codes

Tornado codes simpler to decode/encode but memory requirement is non-deterministic (shown to fare better than RS)

Reed-Solomon codes have fixed memory requirement, but computationally very expensive.

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Questions …