18,954 research outputs found
A Low-Complexity Approach to Distributed Cooperative Caching with Geographic Constraints
We consider caching in cellular networks in which each base station is
equipped with a cache that can store a limited number of files. The popularity
of the files is known and the goal is to place files in the caches such that
the probability that a user at an arbitrary location in the plane will find the
file that she requires in one of the covering caches is maximized.
We develop distributed asynchronous algorithms for deciding which contents to
store in which cache. Such cooperative algorithms require communication only
between caches with overlapping coverage areas and can operate in asynchronous
manner. The development of the algorithms is principally based on an
observation that the problem can be viewed as a potential game. Our basic
algorithm is derived from the best response dynamics. We demonstrate that the
complexity of each best response step is independent of the number of files,
linear in the cache capacity and linear in the maximum number of base stations
that cover a certain area. Then, we show that the overall algorithm complexity
for a discrete cache placement is polynomial in both network size and catalog
size. In practical examples, the algorithm converges in just a few iterations.
Also, in most cases of interest, the basic algorithm finds the best Nash
equilibrium corresponding to the global optimum. We provide two extensions of
our basic algorithm based on stochastic and deterministic simulated annealing
which find the global optimum.
Finally, we demonstrate the hit probability evolution on real and synthetic
networks numerically and show that our distributed caching algorithm performs
significantly better than storing the most popular content, probabilistic
content placement policy and Multi-LRU caching policies.Comment: 24 pages, 9 figures, presented at SIGMETRICS'1
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
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
Efficient Proactive Caching for Supporting Seamless Mobility
We present a distributed proactive caching approach that exploits user
mobility information to decide where to proactively cache data to support
seamless mobility, while efficiently utilizing cache storage using a congestion
pricing scheme. The proposed approach is applicable to the case where objects
have different sizes and to a two-level cache hierarchy, for both of which the
proactive caching problem is hard. Additionally, our modeling framework
considers the case where the delay is independent of the requested data object
size and the case where the delay is a function of the object size. Our
evaluation results show how various system parameters influence the delay gains
of the proposed approach, which achieves robust and good performance relative
to an oracle and an optimal scheme for a flat cache structure.Comment: 10 pages, 9 figure
Secure Partial Repair in Wireless Caching Networks with Broadcast Channels
We study security in partial repair in wireless caching networks where parts
of the stored packets in the caching nodes are susceptible to be erased. Let us
denote a caching node that has lost parts of its stored packets as a sick
caching node and a caching node that has not lost any packet as a healthy
caching node. In partial repair, a set of caching nodes (among sick and healthy
caching nodes) broadcast information to other sick caching nodes to recover the
erased packets. The broadcast information from a caching node is assumed to be
received without any error by all other caching nodes. All the sick caching
nodes then are able to recover their erased packets, while using the broadcast
information and the nonerased packets in their storage as side information. In
this setting, if an eavesdropper overhears the broadcast channels, it might
obtain some information about the stored file. We thus study secure partial
repair in the senses of information-theoretically strong and weak security. In
both senses, we investigate the secrecy caching capacity, namely, the maximum
amount of information which can be stored in the caching network such that
there is no leakage of information during a partial repair process. We then
deduce the strong and weak secrecy caching capacities, and also derive the
sufficient finite field sizes for achieving the capacities. Finally, we propose
optimal secure codes for exact partial repair, in which the recovered packets
are exactly the same as erased packets.Comment: To Appear in IEEE Conference on Communication and Network Security
(CNS
Optimizing The Spatial Content Caching Distribution for Device-to-Device Communications
We study the optimal geographic content placement problem for
device-to-device (D2D) networks in which the content popularity follows the
Zipf law. We consider a D2D caching model where the locations of the D2D users
(caches) are modeled by a Poisson point process (PPP) and have limited
communication range and finite storage. Unlike most related work which assumes
independent placement of content, and does not capture the locations of the
users, we model the spatial properties of the network including spatial
correlation in terms of the cached content. We propose two novel spatial
correlation models, the exchangeable content model and a Mat\'{e}rn (MHC)
content placement model, and analyze and optimize the \emph{hit probability},
which is the probability of a given D2D node finding a desired file at another
node within its communication range. We contrast these results to the
independent placement model, and show that exchangeable placement performs
worse. On the other hand, MHC placement yields a higher cache hit probability
than independent placement for small cache sizes.Comment: appeared in Proc. IEEE Intl. Symposium on Info. Theory, Barcelona,
Spain, July 201
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