Fundamental Limits of Caching
TLDR
This paper proposes a novel coded caching scheme that exploits both local and global caching gains, leading to a multiplicative improvement in the peak rate compared with previously known schemes, and argues that the performance of the proposed scheme is within a constant factor of the information-theoretic optimum for all values of the problem parameters.Abstract:
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 with previously known schemes. In particular, the improvement can be on the order of the number of users in the network. In addition, 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.read more
Citations
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On the Optimality of Uncoded Cache Placement
TL;DR: This paper connects the caching problem to an index coding problem and shows the optimality of the MAN scheme under the conditions that (i) the cache placement phase is restricted to be uncoded (i.e, pieces of the files can only copied into the user's cache), and (ii) the number of users is no more than theNumber of files.
Proceedings Article
Coded MapReduce
TL;DR: Coded MapReduce as mentioned in this paper exploits the repetitive mapping of data blocks at different servers to create coded multicasting opportunities in the shuffling phase, cutting down the total communication load by a multiplicative factor.
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Cache-Aided Interference Channels
TL;DR: In this article, the authors consider an interference channel in which each transmitter is equipped with an isolated cache memory, and they show that through careful joint design of these phases, they can reap three distinct benefits from caching: a load balancing gain, an interference cancellation gain and an interference alignment gain.
Journal ArticleDOI
On the Placement Delivery Array Design in Centralized Coded Caching Scheme
TL;DR: The placement delivery array (PDA) design problem is first formulated to characterize the placement issue and the delivery issue with a single array and it is shown that, through designing appropriate PDA, new centralized coded caching schemes can be discovered.
Proceedings ArticleDOI
Learning distributed caching strategies in small cell networks
TL;DR: This paper proposes a coded caching framework, where the sBSs learn the popularity profile of the files (based on their demand history) via a combinatorial multi-armed bandit framework and modeled as a linear program that takes into account the network connectivity and thereby jointly designs the caching strategies.
References
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Journal ArticleDOI
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