GLOBECOM 2017 - 2017 IEEE Global Communications Conference 2017
DOI: 10.1109/glocom.2017.8254035
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Femto-Caching with Soft Cache Hits: Improving Performance with Related Content Recommendation

Abstract: Pushing popular content to cheap "helper" nodes (e.g., small cells) during off-peak hours has recently been proposed to cope with the increase in mobile data traffic. User requests can be served locally from these helper nodes, if the requested content is available in at least one of the nearby helpers. Nevertheless, the collective storage of a few nearby helper nodes does not usually suffice to achieve a high enough hit rate in practice. We propose to depart from the assumption of hard cache hits, common in e… Show more

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Cited by 27 publications
(39 citation statements)
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“…Caching and Recommendations. The interplay between recommendation systems and caching has been only recently considered in literature, e.g., for peer-to-peer networks [45], CDNs [46], [47], or mobile/cellular networks [24], [26], [27], [25]. Closer to our study, are the works in [47], [26], [27], [24] that consider the promotion/recommendation of contents towards maximizing the probability of hitting a local cache.…”
Section: Related Workmentioning
confidence: 96%
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“…Caching and Recommendations. The interplay between recommendation systems and caching has been only recently considered in literature, e.g., for peer-to-peer networks [45], CDNs [46], [47], or mobile/cellular networks [24], [26], [27], [25]. Closer to our study, are the works in [47], [26], [27], [24] that consider the promotion/recommendation of contents towards maximizing the probability of hitting a local cache.…”
Section: Related Workmentioning
confidence: 96%
“…The caching policy in [27] is based on machine learning techniques, the users' behavior is estimated through the users' interaction with the recommendations and this knowledge is being exploited at the next BS cache updates. Finally, [24] studies the problem of recommendation-aware caching (in contrast to cacheaware recommendations in this paper). Assuming a content provider/service that offers alternative content recommendation or delivery, [24] proposes near-optimal approximation algorithms for content placement in mobile networks with single-cell and multi-cell (e.g., similarly to [10]) user association.…”
Section: Related Workmentioning
confidence: 99%
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“…A literatura sobre o impacto de sistemas de recomendação no desempenho de caches aindaé escassa, mas está rapidamente crescendo [Verhoeyen et al, 2012, Krishnappa et al, 2015, Chatzieleftheriou et al, 2017, Sermpezis et al, 2017.…”
Section: Trabalhos Relacionadosunclassified