English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

This paper develops a stochastic geometry-based approach for the modeling,analysis, and optimization of wireless cloud caching networks comprised ofmultiple-antenna radio units (RUs) inside clouds. We consider the Materncluster process to model RUs and the probabilistic content placement to cachefiles in RUs. Accordingly, we study the exact hit probability for a user ofinterest for two strategies; closest selection, where the user is served by theclosest RU that has its requested file, and best selection, where the servingRU having the requested file provides the maximum instantaneous received powerat the user. As key steps for the analyses, the Laplace transform of out ofcloud interference, the desired link distance distribution in the closestselection, and the desired link received power distribution in the bestselection are derived. Also, we approximate the derived exact hit probabilitiesfor both the closest and the best selections in such a way that the relatedobjective functions for the content caching design of the network can lead totractable concave optimization problems. Solving the optimization problems, wepropose algorithms to efficiently find their optimal content placements.Finally, we investigate the impact of different parameters such as the numberof antennas and the cache memory size on the caching performance.

Stochastic Design and Analysis of Wireless Cloud Caching Networks