1,951 research outputs found
Network Coding in a Multicast Switch
We consider the problem of serving multicast flows in a crossbar switch. We
show that linear network coding across packets of a flow can sustain traffic
patterns that cannot be served if network coding were not allowed. Thus,
network coding leads to a larger rate region in a multicast crossbar switch. We
demonstrate a traffic pattern which requires a switch speedup if coding is not
allowed, whereas, with coding the speedup requirement is eliminated completely.
In addition to throughput benefits, coding simplifies the characterization of
the rate region. We give a graph-theoretic characterization of the rate region
with fanout splitting and intra-flow coding, in terms of the stable set
polytope of the 'enhanced conflict graph' of the traffic pattern. Such a
formulation is not known in the case of fanout splitting without coding. We
show that computing the offline schedule (i.e. using prior knowledge of the
flow arrival rates) can be reduced to certain graph coloring problems. Finally,
we propose online algorithms (i.e. using only the current queue occupancy
information) for multicast scheduling based on our graph-theoretic formulation.
In particular, we show that a maximum weighted stable set algorithm stabilizes
the queues for all rates within the rate region.Comment: 9 pages, submitted to IEEE INFOCOM 200
Speeding Multicast by Acknowledgment Reduction Technique (SMART)
We present a novel feedback protocol for wireless broadcast networks that
utilize linear network coding. We consider transmission of packets from one
source to many receivers over a single-hop broadcast erasure channel. Our
method utilizes a predictive model to request feedback only when the
probability that all receivers have completed decoding is significant. In
addition, our proposed NACK-based feedback mechanism enables all receivers to
request, within a single time slot, the number of retransmissions needed for
successful decoding. We present simulation results as well as analytical
results that show the favorable scalability of our technique as the number of
receivers, file size, and packet erasure probability increase. We also show the
robustness of this scheme to uncertainty in the predictive model, including
uncertainty in the number of receiving nodes and the packet erasure
probability, as well as to losses of the feedback itself. Our scheme, SMART, is
shown to perform nearly as well as an omniscient transmitter that requires no
feedback. Furthermore, SMART, is shown to outperform current state of the art
methods at any given erasure probability, file size, and numbers of receivers
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