377 research outputs found
Fundamental Limits of Caching in Wireless D2D Networks
We consider a wireless Device-to-Device (D2D) network where communication is
restricted to be single-hop. Users make arbitrary requests from a finite
library of files and have pre-cached information on their devices, subject to a
per-node storage capacity constraint. A similar problem has already been
considered in an ``infrastructure'' setting, where all users receive a common
multicast (coded) message from a single omniscient server (e.g., a base station
having all the files in the library) through a shared bottleneck link. In this
work, we consider a D2D ``infrastructure-less'' version of the problem. We
propose a caching strategy based on deterministic assignment of subpackets of
the library files, and a coded delivery strategy where the users send linearly
coded messages to each other in order to collectively satisfy their demands. We
also consider a random caching strategy, which is more suitable to a fully
decentralized implementation. Under certain conditions, both approaches can
achieve the information theoretic outer bound within a constant multiplicative
factor. In our previous work, we showed that a caching D2D wireless network
with one-hop communication, random caching, and uncoded delivery, achieves the
same throughput scaling law of the infrastructure-based coded multicasting
scheme, in the regime of large number of users and files in the library. This
shows that the spatial reuse gain of the D2D network is order-equivalent to the
coded multicasting gain of single base station transmission. It is therefore
natural to ask whether these two gains are cumulative, i.e.,if a D2D network
with both local communication (spatial reuse) and coded multicasting can
provide an improved scaling law. Somewhat counterintuitively, we show that
these gains do not cumulate (in terms of throughput scaling law).Comment: 45 pages, 5 figures, Submitted to IEEE Transactions on Information
Theory, This is the extended version of the conference (ITW) paper
arXiv:1304.585
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
Decentralized Coded Caching Attains Order-Optimal Memory-Rate Tradeoff
Replicating or caching popular content in memories distributed across the
network is a technique to reduce peak network loads. Conventionally, the main
performance gain of this caching was thought to result from making part of the
requested data available closer to end users. Instead, we recently showed that
a much more significant gain can be achieved by using caches to create
coded-multicasting opportunities, even for users with different demands,
through coding across data streams. These coded-multicasting opportunities are
enabled by careful content overlap at the various caches in the network,
created by a central coordinating server.
In many scenarios, such a central coordinating server may not be available,
raising the question if this multicasting gain can still be achieved in a more
decentralized setting. In this paper, we propose an efficient caching scheme,
in which the content placement is performed in a decentralized manner. In other
words, no coordination is required for the content placement. Despite this lack
of coordination, the proposed scheme is nevertheless able to create
coded-multicasting opportunities and achieves a rate close to the optimal
centralized scheme.Comment: To appear in IEEE/ACM Transactions on Networkin
On Caching with More Users than Files
Caching appears to be an efficient way to reduce peak hour network traffic
congestion by storing some content at the user's cache without knowledge of
later demands. Recently, Maddah-Ali and Niesen proposed a two-phase, placement
and delivery phase, coded caching strategy for centralized systems (where
coordination among users is possible in the placement phase), and for
decentralized systems. This paper investigates the same setup under the further
assumption that the number of users is larger than the number of files. By
using the same uncoded placement strategy of Maddah-Ali and Niesen, a novel
coded delivery strategy is proposed to profit from the multicasting
opportunities that arise because a file may be demanded by multiple users. The
proposed delivery method is proved to be optimal under the constraint of
uncoded placement for centralized systems with two files, moreover it is shown
to outperform known caching strategies for both centralized and decentralized
systems.Comment: 6 pages, 3 figures, submitted to ISIT 201
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
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