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Open AccessFeature PaperArticle

Cache-Aided General Linear Function Retrieval

1
Electrical Engineering and Computer Science Department, Technische Universität Berlin, 10587 Berlin, Germany
2
Department of Electrical Engineering, University of North Texas, Denton, TX 76203, USA
3
Electrical and Computer Engineering Department, University of Utah, Salt Lake City, UT 84112, USA
4
Electrical and Computer Engineering Department, University of Illinois Chicago, Chicago, IL 60607, USA
*
Author to whom correspondence should be addressed.
Entropy 2021, 23(1), 25; https://doi.org/10.3390/e23010025
Received: 7 November 2020 / Revised: 22 December 2020 / Accepted: 22 December 2020 / Published: 26 December 2020
Coded Caching, proposed by Maddah-Ali and Niesen (MAN), has the potential to reduce network traffic by pre-storing content in the users’ local memories when the network is underutilized and transmitting coded multicast messages that simultaneously benefit many users at once during peak-hour times. This paper considers the linear function retrieval version of the original coded caching setting, where users are interested in retrieving a number of linear combinations of the data points stored at the server, as opposed to a single file. This extends the scope of the authors’ past work that only considered the class of linear functions that operate element-wise over the files. On observing that the existing cache-aided scalar linear function retrieval scheme does not work in the proposed setting, this paper designs a novel coded caching scheme that outperforms uncoded caching schemes that either use unicast transmissions or let each user recover all files in the library. View Full-Text
Keywords: coded caching; linear function retrieval; uncoded cache placement coded caching; linear function retrieval; uncoded cache placement
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MDPI and ACS Style

Wan, K.; Sun, H.; Ji, M.; Tuninetti, D.; Caire, G. Cache-Aided General Linear Function Retrieval. Entropy 2021, 23, 25. https://doi.org/10.3390/e23010025

AMA Style

Wan K, Sun H, Ji M, Tuninetti D, Caire G. Cache-Aided General Linear Function Retrieval. Entropy. 2021; 23(1):25. https://doi.org/10.3390/e23010025

Chicago/Turabian Style

Wan, Kai; Sun, Hua; Ji, Mingyue; Tuninetti, Daniela; Caire, Giuseppe. 2021. "Cache-Aided General Linear Function Retrieval" Entropy 23, no. 1: 25. https://doi.org/10.3390/e23010025

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