37 research outputs found
Caching and Coded Multicasting: Multiple Groupcast Index Coding
The capacity of caching networks has received considerable attention in the
past few years. A particularly studied setting is the case of a single server
(e.g., a base station) and multiple users, each of which caches segments of
files in a finite library. Each user requests one (whole) file in the library
and the server sends a common coded multicast message to satisfy all users at
once. The problem consists of finding the smallest possible codeword length to
satisfy such requests. In this paper we consider the generalization to the case
where each user places requests. The obvious naive scheme consists
of applying times the order-optimal scheme for a single request, obtaining
a linear in scaling of the multicast codeword length. We propose a new
achievable scheme based on multiple groupcast index coding that achieves a
significant gain over the naive scheme. Furthermore, through an information
theoretic converse we find that the proposed scheme is approximately optimal
within a constant factor of (at most) .Comment: 5 pages, 1 figure, to appear in GlobalSIP14, Dec. 201
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
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
Performance of Caching-Based D2D Video Distribution with Measured Popularity Distributions
On-demand video accounts for the majority of wireless data traffic. Video
distribution schemes based on caching combined with device-to-device (D2D)
communications promise order-of-magnitude greater spectral efficiency for video
delivery, but hinge on the principle of `concentrated demand distributions.'
This paper presents, for the first time, the analysis and evaluations of the
throughput--outage tradeoff of such schemes based on measured cellular demand
distributions. In particular, we use a dataset with more than 100 million
requests from the BBC iPlayer, a popular video streaming service in the U.K.,
as the foundation of the analysis and evaluations. We present an achievable
scaling law based on the practical popularity distribution, and show that such
scaling law is identical to those reported in the literature. We find that also
for the numerical evaluations based on a realistic setup, order-of-magnitude
improvements can be achieved. Our results indicate that the benefits promised
by the caching-based D2D in the literature could be retained for cellular
networks in practice.Comment: Submitted to IEEE Globecom 201