1,869 research outputs found
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
Broadcast Caching Networks with Two Receivers and Multiple Correlated Sources
The correlation among the content distributed across a cache-aided broadcast
network can be exploited to reduce the delivery load on the shared wireless
link. This paper considers a two-user three-file network with correlated
content, and studies its fundamental limits for the worst-case demand. A class
of achievable schemes based on a two-step source coding approach is proposed.
Library files are first compressed using Gray-Wyner source coding, and then
cached and delivered using a combination of correlation-unaware cache-aided
coded multicast schemes. The second step is interesting in its own right and
considers a multiple-request caching problem, whose solution requires coding in
the placement phase. A lower bound on the optimal peak rate-memory trade-off is
derived, which is used to evaluate the performance of the proposed scheme. It
is shown that for symmetric sources the two-step strategy achieves the lower
bound for large cache capacities, and it is within half of the joint entropy of
two of the sources conditioned on the third source for all other cache sizes.Comment: in Proceedings of Asilomar Conference on Signals, Systems and
Computers, Pacific Grove, California, November 201
Cache-Aided Coded Multicast for Correlated Sources
The combination of edge caching and coded multicasting is a promising
approach to improve the efficiency of content delivery over cache-aided
networks. The global caching gain resulting from content overlap distributed
across the network in current solutions is limited due to the increasingly
personalized nature of the content consumed by users. In this paper, the
cache-aided coded multicast problem is generalized to account for the
correlation among the network content by formulating a source compression
problem with distributed side information. A correlation-aware achievable
scheme is proposed and an upper bound on its performance is derived. It is
shown that considerable load reductions can be achieved, compared to state of
the art correlation-unaware schemes, when caching and delivery phases
specifically account for the correlation among the content files.Comment: In proceeding of IEEE International Symposium on Turbo Codes and
Iterative Information Processing (ISTC), 201
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
Correlation-Aware Distributed Caching and Coded Delivery
Cache-aided coded multicast leverages side information at wireless edge
caches to efficiently serve multiple groupcast demands via common multicast
transmissions, leading to load reductions that are proportional to the
aggregate cache size. However, the increasingly unpredictable and personalized
nature of the content that users consume challenges the efficiency of existing
caching-based solutions in which only exact content reuse is explored. This
paper generalizes the cache-aided coded multicast problem to a source
compression with distributed side information problem that specifically
accounts for the correlation among the content files. It is shown how joint
file compression during the caching and delivery phases can provide load
reductions that go beyond those achieved with existing schemes. This is
accomplished through a lower bound on the fundamental rate-memory trade-off as
well as a correlation-aware achievable scheme, shown to significantly
outperform state-of-the-art correlation-unaware solutions, while approaching
the limiting rate-memory trade-off.Comment: In proceeding of IEEE Information Theory Workshop (ITW), 201
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