350 research outputs found
On the Average Performance of Caching and Coded Multicasting with Random Demands
For a network with one sender, receivers (users) and possible
messages (files), caching side information at the users allows to satisfy
arbitrary simultaneous demands by sending a common (multicast) coded message.
In the worst-case demand setting, explicit deterministic and random caching
strategies and explicit linear coding schemes have been shown to be order
optimal. In this work, we consider the same scenario where the user demands are
random i.i.d., according to a Zipf popularity distribution. In this case, we
pose the problem in terms of the minimum average number of equivalent message
transmissions. We present a novel decentralized random caching placement and a
coded delivery scheme which are shown to achieve order-optimal performance. As
a matter of fact, this is the first order-optimal result for the caching and
coded multicasting problem in the case of random demands.Comment: 5 pages, 3 figure, to appear in ISWCS 201
Distortion-Memory Tradeoffs in Cache-Aided Wireless Video Delivery
Mobile network operators are considering caching as one of the strategies to
keep up with the increasing demand for high-definition wireless video
streaming. By prefetching popular content into memory at wireless access points
or end user devices, requests can be served locally, relieving strain on
expensive backhaul. In addition, using network coding allows the simultaneous
serving of distinct cache misses via common coded multicast transmissions,
resulting in significantly larger load reductions compared to those achieved
with conventional delivery schemes. However, prior work does not exploit the
properties of video and simply treats content as fixed-size files that users
would like to fully download. Our work is motivated by the fact that video can
be coded in a scalable fashion and that the decoded video quality depends on
the number of layers a user is able to receive. Using a Gaussian source model,
caching and coded delivery methods are designed to minimize the squared error
distortion at end user devices. Our work is general enough to consider
heterogeneous cache sizes and video popularity distributions.Comment: To appear in Allerton 2015 Proceedings of the 53rd annual Allerton
conference on Communication, control, and computin
An Efficient Coded Multicasting Scheme Preserving the Multiplicative Caching Gain
Coded multicasting has been shown to be a promis- ing approach to
significantly improve the caching performance of content delivery networks with
multiple caches downstream of a common multicast link. However, achievable
schemes proposed to date have been shown to achieve the proved order-optimal
performance only in the asymptotic regime in which the number of packets per
requested item goes to infinity. In this paper, we first extend the asymptotic
analysis of the achievable scheme in [1], [2] to the case of heterogeneous
cache sizes and demand distributions, providing the best known upper bound on
the fundamental limiting performance when the number of packets goes to
infinity. We then show that the scheme achieving this upper bound quickly loses
its multiplicative caching gain for finite content packetization. To overcome
this limitation, we design a novel polynomial-time algorithm based on random
greedy graph- coloring that, while keeping the same finite content
packetization, recovers a significant part of the multiplicative caching gain.
Our results show that the order-optimal coded multicasting schemes proposed to
date, while useful in quantifying the fundamental limiting performance, must be
properly designed for practical regimes of finite packetization.Comment: 6 pages, 7 figures, Published in Infocom CNTCV 201
Speeding up Future Video Distribution via Channel-Aware Caching-Aided Coded Multicast
Future Internet usage will be dominated by the consumption of a rich variety
of online multimedia services accessed from an exponentially growing number of
multimedia capable mobile devices. As such, future Internet designs will be
challenged to provide solutions that can deliver bandwidth-intensive,
delay-sensitive, on-demand video-based services over increasingly crowded,
bandwidth-limited wireless access networks. One of the main reasons for the
bandwidth stress facing wireless network operators is the difficulty to exploit
the multicast nature of the wireless medium when wireless users or access
points rarely experience the same channel conditions or access the same content
at the same time. In this paper, we present and analyze a novel wireless video
delivery paradigm based on the combined use of channel-aware caching and coded
multicasting that allows simultaneously serving multiple cache-enabled
receivers that may be requesting different content and experiencing different
channel conditions. To this end, we reformulate the caching-aided coded
multicast problem as a joint source-channel coding problem and design an
achievable scheme that preserves the cache-enabled multiplicative throughput
gains of the error-free scenario,by guaranteeing per-receiver rates unaffected
by the presence of receivers with worse channel conditions.Comment: 11 pages,6 figures,to appear in IEEE JSAC Special Issue on Video
Distribution over Future Interne
Finite Length Analysis of Caching-Aided Coded Multicasting
In this work, we study a noiseless broadcast link serving users whose
requests arise from a library of files. Every user is equipped with a cache
of size files each. It has been shown that by splitting all the files into
packets and placing individual packets in a random independent manner across
all the caches, it requires at most file transmissions for any set of
demands from the library. The achievable delivery scheme involves linearly
combining packets of different files following a greedy clique cover solution
to the underlying index coding problem. This remarkable multiplicative gain of
random placement and coded delivery has been established in the asymptotic
regime when the number of packets per file scales to infinity.
In this work, we initiate the finite-length analysis of random caching
schemes when the number of packets is a function of the system parameters
. Specifically, we show that existing random placement and clique cover
delivery schemes that achieve optimality in the asymptotic regime can have at
most a multiplicative gain of if the number of packets is sub-exponential.
Further, for any clique cover based coded delivery and a large class of random
caching schemes, that includes the existing ones, we show that the number of
packets required to get a multiplicative gain of is at least
. We exhibit a random placement and an efficient clique cover based
coded delivery scheme that approximately achieves this lower bound. We also
provide tight concentration results that show that the average (over the random
caching involved) number of transmissions concentrates very well requiring only
polynomial number of packets in the rest of the parameters.Comment: A shorter version appeared in the 52nd Annual Allerton Conference on
Communication, Control, and Computing (Allerton), 201
Online Coded Caching
We consider a basic content distribution scenario consisting of a single
origin server connected through a shared bottleneck link to a number of users
each equipped with a cache of finite memory. The users issue a sequence of
content requests from a set of popular files, and the goal is to operate the
caches as well as the server such that these requests are satisfied with the
minimum number of bits sent over the shared link. Assuming a basic Markov model
for renewing the set of popular files, we characterize approximately the
optimal long-term average rate of the shared link. We further prove that the
optimal online scheme has approximately the same performance as the optimal
offline scheme, in which the cache contents can be updated based on the entire
set of popular files before each new request. To support these theoretical
results, we propose an online coded caching scheme termed coded least-recently
sent (LRS) and simulate it for a demand time series derived from the dataset
made available by Netflix for the Netflix Prize. For this time series, we show
that the proposed coded LRS algorithm significantly outperforms the popular
least-recently used (LRU) caching algorithm.Comment: 15 page
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