2,442 research outputs found
A New Stable Peer-to-Peer Protocol with Non-persistent Peers
Recent studies have suggested that the stability of peer-to-peer networks may
rely on persistent peers, who dwell on the network after they obtain the entire
file. In the absence of such peers, one piece becomes extremely rare in the
network, which leads to instability. Technological developments, however, are
poised to reduce the incidence of persistent peers, giving rise to a need for a
protocol that guarantees stability with non-persistent peers. We propose a
novel peer-to-peer protocol, the group suppression protocol, to ensure the
stability of peer-to-peer networks under the scenario that all the peers adopt
non-persistent behavior. Using a suitable Lyapunov potential function, the
group suppression protocol is proven to be stable when the file is broken into
two pieces, and detailed experiments demonstrate the stability of the protocol
for arbitrary number of pieces. We define and simulate a decentralized version
of this protocol for practical applications. Straightforward incorporation of
the group suppression protocol into BitTorrent while retaining most of
BitTorrent's core mechanisms is also presented. Subsequent simulations show
that under certain assumptions, BitTorrent with the official protocol cannot
escape from the missing piece syndrome, but BitTorrent with group suppression
does.Comment: There are only a couple of minor changes in this version. Simulation
tool is specified this time. Some repetitive figures are remove
Refinement of the random coding bound
An improved pre-factor for the random coding bound is proved. Specifically,
for channels with critical rate not equal to capacity, if a regularity
condition is satisfied (resp. not satisfied), then for any a
pre-factor of (resp. ) is achievable for rates above the
critical rate, where and is the blocklength and rate, respectively. The
extra term is related to the slope of the random coding
exponent. Further, the relation of these bounds with the authors' recent
refinement of the sphere-packing bound, as well as the pre-factor for the
random coding bound below the critical rate, is discussed.Comment: Submitted to IEEE Trans. Inform. Theor
A Rate-Distortion Approach to Index Coding
We approach index coding as a special case of rate-distortion with multiple
receivers, each with some side information about the source. Specifically,
using techniques developed for the rate-distortion problem, we provide two
upper bounds and one lower bound on the optimal index coding rate. The upper
bounds involve specific choices of the auxiliary random variables in the best
existing scheme for the rate-distortion problem. The lower bound is based on a
new lower bound for the general rate-distortion problem. The bounds are shown
to coincide for a number of (groupcast) index coding instances, including all
instances for which the number of decoders does not exceed three.Comment: Substantially extended version. Submitted to IEEE Transactions on
Information Theor
The third-order term in the normal approximation for singular channels
For a singular and symmetric discrete memoryless channel with positive
dispersion, the third-order term in the normal approximation is shown to be
upper bounded by a constant. This finding completes the characterization of the
third-order term for symmetric discrete memoryless channels. The proof method
is extended to asymmetric and singular channels with constant composition
codes, and its connection to existing results, as well as its limitation in the
error exponents regime, are discussed.Comment: Submitted to IEEE Trans. Inform. Theor
Erasure Multiple Descriptions
We consider a binary erasure version of the n-channel multiple descriptions
problem with symmetric descriptions, i.e., the rates of the n descriptions are
the same and the distortion constraint depends only on the number of messages
received. We consider the case where there is no excess rate for every k out of
n descriptions. Our goal is to characterize the achievable distortions D_1,
D_2,...,D_n. We measure the fidelity of reconstruction using two distortion
criteria: an average-case distortion criterion, under which distortion is
measured by taking the average of the per-letter distortion over all source
sequences, and a worst-case distortion criterion, under which distortion is
measured by taking the maximum of the per-letter distortion over all source
sequences. We present achievability schemes, based on random binning for
average-case distortion and systematic MDS (maximum distance separable) codes
for worst-case distortion, and prove optimality results for the corresponding
achievable distortion regions. We then use the binary erasure multiple
descriptions setup to propose a layered coding framework for multiple
descriptions, which we then apply to vector Gaussian multiple descriptions and
prove its optimality for symmetric scalar Gaussian multiple descriptions with
two levels of receivers and no excess rate for the central receiver. We also
prove a new outer bound for the general multi-terminal source coding problem
and use it to prove an optimality result for the robust binary erasure CEO
problem. For the latter, we provide a tight lower bound on the distortion for
\ell messages for any coding scheme that achieves the minimum achievable
distortion for k messages where k is less than or equal to \ell.Comment: 48 pages, 2 figures, submitted to IEEE Trans. Inf. Theor
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