4,285 research outputs found
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
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
Coded Caching for a Large Number Of Users
Information theoretic analysis of a coded caching system is considered, in
which a server with a database of N equal-size files, each F bits long, serves
K users. Each user is assumed to have a local cache that can store M files,
i.e., capacity of MF bits. Proactive caching to user terminals is considered,
in which the caches are filled by the server in advance during the placement
phase, without knowing the user requests. Each user requests a single file, and
all the requests are satisfied simultaneously through a shared error-free link
during the delivery phase.
First, centralized coded caching is studied assuming both the number and the
identity of the active users in the delivery phase are known by the server
during the placement phase. A novel group-based centralized coded caching (GBC)
scheme is proposed for a cache capacity of M = N/K. It is shown that this
scheme achieves a smaller delivery rate than all the known schemes in the
literature. The improvement is then extended to a wider range of cache
capacities through memory-sharing between the proposed scheme and other known
schemes in the literature. Next, the proposed centralized coded caching idea is
exploited in the decentralized setting, in which the identities of the users
that participate in the delivery phase are assumed to be unknown during the
placement phase. It is shown that the proposed decentralized caching scheme
also achieves a delivery rate smaller than the state-of-the-art. Numerical
simulations are also presented to corroborate our theoretical results
Fundamental Limits of Caching with Secure Delivery
Caching is emerging as a vital tool for alleviating the severe capacity
crunch in modern content-centric wireless networks. The main idea behind
caching is to store parts of popular content in end-users' memory and leverage
the locally stored content to reduce peak data rates. By jointly designing
content placement and delivery mechanisms, recent works have shown order-wise
reduction in transmission rates in contrast to traditional methods. In this
work, we consider the secure caching problem with the additional goal of
minimizing information leakage to an external wiretapper. The fundamental cache
memory vs. transmission rate trade-off for the secure caching problem is
characterized. Rather surprisingly, these results show that security can be
introduced at a negligible cost, particularly for large number of files and
users. It is also shown that the rate achieved by the proposed caching scheme
with secure delivery is within a constant multiplicative factor from the
information-theoretic optimal rate for almost all parameter values of practical
interest
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