174 research outputs found
Caching in Combination Networks: Novel Multicast Message Generation and Delivery by Leveraging the Network Topology
Maddah-Ali and Niesen's original coded caching scheme for shared-link
broadcast networks is now known to be optimal to within a factor two, and has
been applied to other types of networks. For practical reasons, this paper
considers that a server communicates to cache-aided users through
intermediate relays. In particular, it focuses on combination networks where
each of the users is connected to a distinct -subsets of
relays. By leveraging the symmetric topology of the network, this paper
proposes a novel method to general multicast messages and to deliver them to
the users. By numerical evaluations, the proposed scheme is shown to reduce the
download time compared to the schemes available in the literature. The idea is
then extended to decentralized combination networks, more general relay
networks, and combination networks with cache-aided relays and users. Also in
these cases the proposed scheme outperforms known ones.Comment: 6 pages, 3 figures, accepted in ICC 2018, correct the typo in (6) of
the previous versio
Generalized Degrees of Freedom of the Symmetric Cache-Aided MISO Broadcast Channel with Partial CSIT
We consider the cache-aided MISO broadcast channel (BC) in which a
multi-antenna transmitter serves single-antenna receivers, each equipped
with a cache memory. The transmitter has access to partial knowledge of the
channel state information. For a symmetric setting, in terms of channel
strength levels, partial channel knowledge levels and cache sizes, we
characterize the generalized degrees of freedom (GDoF) up to a constant
multiplicative factor. The achievability scheme exploits the interplay between
spatial multiplexing gains and coded-multicasting gain. On the other hand, a
cut-set-based argument in conjunction with a GDoF outer bound for a parallel
MISO BC under channel uncertainty are used for the converse. We further show
that the characterized order-optimal GDoF is also attained in a decentralized
setting, where no coordination is required for content placement in the caches.Comment: first revisio
Fundamental Limits of Caching
Caching is a technique to reduce peak traffic rates by prefetching popular
content into memories at the end users. Conventionally, these memories are used
to deliver requested content in part from a locally cached copy rather than
through the network. The gain offered by this approach, which we term local
caching gain, depends on the local cache size (i.e, the memory available at
each individual user). In this paper, we introduce and exploit a second,
global, caching gain not utilized by conventional caching schemes. This gain
depends on the aggregate global cache size (i.e., the cumulative memory
available at all users), even though there is no cooperation among the users.
To evaluate and isolate these two gains, we introduce an
information-theoretic formulation of the caching problem focusing on its basic
structure. For this setting, we propose a novel coded caching scheme that
exploits both local and global caching gains, leading to a multiplicative
improvement in the peak rate compared to previously known schemes. In
particular, the improvement can be on the order of the number of users in the
network. Moreover, we argue that the performance of the proposed scheme is
within a constant factor of the information-theoretic optimum for all values of
the problem parameters.Comment: To appear in IEEE Transactions on Information Theor
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
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