2,042 research outputs found
Optimizing MDS Codes for Caching at the Edge
In this paper we investigate the problem of optimal MDS-encoded cache
placement at the wireless edge to minimize the backhaul rate in heterogeneous
networks. We derive the backhaul rate performance of any caching scheme based
on file splitting and MDS encoding and we formulate the optimal caching scheme
as a convex optimization problem. We then thoroughly investigate the
performance of this optimal scheme for an important heterogeneous network
scenario. We compare it to several other caching strategies and we analyze the
influence of the system parameters, such as the popularity and size of the
library files and the capabilities of the small-cell base stations, on the
overall performance of our optimal caching strategy. Our results show that the
careful placement of MDS-encoded content in caches at the wireless edge leads
to a significant decrease of the load of the network backhaul and hence to a
considerable performance enhancement of the network.Comment: to appear in Globecom 201
Content Caching and Delivery over Heterogeneous Wireless Networks
Emerging heterogeneous wireless architectures consist of a dense deployment
of local-coverage wireless access points (APs) with high data rates, along with
sparsely-distributed, large-coverage macro-cell base stations (BS). We design a
coded caching-and-delivery scheme for such architectures that equips APs with
storage, enabling content pre-fetching prior to knowing user demands. Users
requesting content are served by connecting to local APs with cached content,
as well as by listening to a BS broadcast transmission. For any given content
popularity profile, the goal is to design the caching-and-delivery scheme so as
to optimally trade off the transmission cost at the BS against the storage cost
at the APs and the user cost of connecting to multiple APs. We design a coded
caching scheme for non-uniform content popularity that dynamically allocates
user access to APs based on requested content. We demonstrate the approximate
optimality of our scheme with respect to information-theoretic bounds. We
numerically evaluate it on a YouTube dataset and quantify the trade-off between
transmission rate, storage, and access cost. Our numerical results also suggest
the intriguing possibility that, to gain most of the benefits of coded caching,
it suffices to divide the content into a small number of popularity classes.Comment: A shorter version is to appear in IEEE INFOCOM 201
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